Alternatives to Amazon FinSpace
Compare Amazon FinSpace alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Amazon FinSpace in 2026. Compare features, ratings, user reviews, pricing, and more from Amazon FinSpace competitors and alternatives in order to make an informed decision for your business.
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RaimaDB
Raima
RaimaDB is an embedded time series database for IoT and Edge devices that can run in-memory. It is an extremely powerful, lightweight and secure RDBMS. Field tested by over 20 000 developers worldwide and has more than 25 000 000 deployments. RaimaDB is a high-performance, cross-platform embedded database designed for mission-critical applications, particularly in the Internet of Things (IoT) and edge computing markets. It offers a small footprint, making it suitable for resource-constrained environments, and supports both in-memory and persistent storage configurations. RaimaDB provides developers with multiple data modeling options, including traditional relational models and direct relationships through network model sets. It ensures data integrity with ACID-compliant transactions and supports various indexing methods such as B+Tree, Hash Table, R-Tree, and AVL-Tree. -
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Amazon EC2
Amazon
Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers. Amazon EC2’s simple web service interface allows you to obtain and configure capacity with minimal friction. It provides you with complete control of your computing resources and lets you run on Amazon’s proven computing environment. Amazon EC2 delivers the broadest choice of compute, networking (up to 400 Gbps), and storage services purpose-built to optimize price performance for ML projects. Build, test, and sign on-demand macOS workloads. Access environments in minutes, dynamically scale capacity as needed, and benefit from AWS’s pay-as-you-go pricing. Access the on-demand infrastructure and capacity you need to run HPC applications faster and cost-effectively. Amazon EC2 delivers secure, reliable, high-performance, and cost-effective compute infrastructure to meet demanding business needs. -
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Amazon WorkSpaces
Amazon
Amazon WorkSpaces is a managed, secure Desktop-as-a-Service (DaaS) solution. You can use Amazon WorkSpaces to provision either Windows or Linux desktops in just a few minutes and quickly scale to provide thousands of desktops to workers across the globe. You can pay either monthly or hourly, just for the WorkSpaces you launch, which helps you save money when compared to traditional desktops and on-premises VDI solutions. Amazon WorkSpaces helps you eliminate the complexity in managing hardware inventory, OS versions and patches, and Virtual Desktop Infrastructure (VDI), which helps simplify your desktop delivery strategy. With Amazon WorkSpaces, your users get a fast, responsive desktop of their choice that they can access anywhere, anytime, from any supported device. Enable contact center agents to work from anywhere with a secure, easy-to-use agent experience. Let contact center agents work from anywhere. -
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Amazon Redshift
Amazon
More customers pick Amazon Redshift than any other cloud data warehouse. Redshift powers analytical workloads for Fortune 500 companies, startups, and everything in between. Companies like Lyft have grown with Redshift from startups to multi-billion dollar enterprises. No other data warehouse makes it as easy to gain new insights from all your data. With Redshift you can query petabytes of structured and semi-structured data across your data warehouse, operational database, and your data lake using standard SQL. Redshift lets you easily save the results of your queries back to your S3 data lake using open formats like Apache Parquet to further analyze from other analytics services like Amazon EMR, Amazon Athena, and Amazon SageMaker. Redshift is the world’s fastest cloud data warehouse and gets faster every year. For performance intensive workloads you can use the new RA3 instances to get up to 3x the performance of any cloud data warehouse.Starting Price: $0.25 per hour -
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AWS Fargate
Amazon
AWS Fargate is a serverless compute engine for containers that works with both Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS). Fargate makes it easy for you to focus on building your applications. Fargate removes the need to provision and manage servers, lets you specify and pay for resources per application, and improves security through application isolation by design. Fargate allocates the right amount of compute, eliminating the need to choose instances and scale cluster capacity. You only pay for the resources required to run your containers, so there is no over-provisioning and paying for additional servers. Fargate runs each task or pod in its own kernel providing the tasks and pods their own isolated compute environment. This enables your application to have workload isolation and improved security by design. -
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Amazon Personalize
Amazon
Amazon Personalize enables developers to build applications with the same machine learning (ML) technology used by Amazon.com for real-time personalized recommendations – no ML expertise required. Amazon Personalize makes it easy for developers to build applications capable of delivering a wide array of personalization experiences, including specific product recommendations, personalized product re-ranking, and customized direct marketing. Amazon Personalize is a fully managed machine learning service that goes beyond rigid static rule based recommendation systems and trains, tunes, and deploys custom ML models to deliver highly customized recommendations to customers across industries such as retail and media and entertainment. Amazon Personalize provisions the necessary infrastructure and manages the entire ML pipeline, including processing the data, identifying features, using the best algorithms, and training, optimizing, and hosting the models. -
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Amazon Timestream
Amazon
Amazon Timestream is a fast, scalable, and serverless time series database service for IoT and operational applications that makes it easy to store and analyze trillions of events per day up to 1,000 times faster and at as little as 1/10th the cost of relational databases. Amazon Timestream saves you time and cost in managing the lifecycle of time series data by keeping recent data in memory and moving historical data to a cost optimized storage tier based upon user defined policies. Amazon Timestream’s purpose-built query engine lets you access and analyze recent and historical data together, without needing to specify explicitly in the query whether the data resides in the in-memory or cost-optimized tier. Amazon Timestream has built-in time series analytics functions, helping you identify trends and patterns in your data in near real-time. -
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kdb Insights
KX
kdb Insights is a cloud-native, high-performance analytics platform designed for real-time analysis of both streaming and historical data. It enables intelligent decision-making regardless of data volume or velocity, offering unmatched price and performance, and delivering analytics up to 100 times faster at 10% of the cost compared to other solutions. The platform supports interactive data visualization through real-time dashboards, facilitating instantaneous insights and decision-making. It also integrates machine learning models to predict, cluster, detect patterns, and score structured data, enhancing AI capabilities on time-series datasets. With supreme scalability, kdb Insights handles extensive real-time and historical data, proven at volumes of up to 110 terabytes per day. Its quick setup and simple data intake accelerate time-to-value, while native support for q, SQL, and Python, along with compatibility with other languages via RESTful APIs. -
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kdb+
KX Systems
A high-performance cross-platform historical time-series columnar database featuring: - An in-memory compute engine - A real-time streaming processor - An expressive query and programming language called q kdb+ powers kdb Insights portfolio and KDB.AI, together delivering time-oriented data insights and generative AI capabilities to the world’s leading enterprise organizations. Independently benchmarked* as the fastest in-memory, columnar analytics database available, kdb+ delivers unmatched value to businesses operating in the toughest data environments. kdb+ improves decision-making processes to help navigate rapidly changing data landscapes. -
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OpenTSDB
OpenTSDB
OpenTSDB consists of a Time Series Daemon (TSD) as well as set of command line utilities. Interaction with OpenTSDB is primarily achieved by running one or more of the independent TSDs. There is no master, no shared state so you can run as many TSDs as required to handle any load you throw at it. Each TSD uses the open source database HBase or hosted Google Bigtable service to store and retrieve time-series data. The data schema is highly optimized for fast aggregations of similar time series to minimize storage space. Users of the TSD never need to access the underlying store directly. You can communicate with the TSD via a simple telnet-style protocol, an HTTP API or a simple built-in GUI. The first step in using OpenTSDB is to send time series data to the TSDs. A number of tools exist to pull data from various sources into OpenTSDB. -
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QuasarDB
QuasarDB
Quasar's brain is QuasarDB, a high-performance, distributed, column-oriented timeseries database management system designed from the ground up to deliver real-time on petascale use cases. Up to 20X less disk usage. Quasardb ingestion and compression capabilities are unmatched. Up to 10,000X faster feature extraction. QuasarDB can extract features in real-time from the raw data, thanks to the combination of a built-in map/reduce query engine, an aggregation engine that leverages SIMD from modern CPUs, and stochastic indexes that use virtually no disk space. The most cost-effective timeseries solution, thanks to its ultra-efficient resource usage, the capability to leverage object storage (S3), unique compression technology, and fair pricing model. Quasar runs everywhere, from 32-bit ARM devices to high-end Intel servers, from Edge Computing to the cloud or on-premises. -
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Azure Time Series Insights
Microsoft
Azure Time Series Insights Gen2 is an open and scalable end-to-end IoT analytics service featuring best-in-class user experiences and rich APIs to integrate its powerful capabilities into your existing workflow or application. You can use it to collect, process, store, query and visualize data at Internet of Things (IoT) scale--data that's highly contextualized and optimized for time series. Azure Time Series Insights Gen2 is designed for ad hoc data exploration and operational analysis allowing you to uncover hidden trends, spotting anomalies, and conduct root-cause analysis. It's an open and flexible offering that meets the broad needs of industrial IoT deployments.Starting Price: $36.208 per unit per month -
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Tiger Data
Tiger Data
Tiger Data is the creator of TimescaleDB, the world’s leading PostgreSQL-based time-series and analytics database. It provides a modern data platform purpose-built for developers, devices, and AI agents. Designed to extend PostgreSQL beyond traditional limits, Tiger Data offers built-in primitives for time-series data, search, materialization, and scale. With features like auto-partitioning, hybrid storage, and compression, it helps teams query billions of rows in milliseconds while cutting infrastructure costs. Tiger Cloud delivers these capabilities as a fully managed, elastic environment with enterprise-grade security and compliance. Trusted by innovators like Cloudflare, Toyota, Polymarket, and Hugging Face, Tiger Data powers real-time analytics, observability, and intelligent automation across industries.Starting Price: $30 per month -
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SellerSpace
SellerSpace
SellerSpace is a SaaS designed to empower Amazon sellers and streamline their operations. It addresses key seller pains:sales tracking, advertising optimization, business insight, profit analysis, hijacking monitoring and more. SellerSpace integrates all aspects of your Amazon business – store, product, advertising, operations, finance, and FBA inventory – covering virtually every operational scenario. With a particular focus on advertising, SellerSpace offers powerful yet user-friendly tools to help sellers easily manage campaigns and max their advertising ROI. Access across Web, extension, and mobile App,SellerSpace provides multi-platform support to optimize your entire Amazon business and drive sustainable growth.Starting Price: $19.9/month -
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Amazon Bedrock AgentCore
Amazon
Amazon Bedrock AgentCore enables you to deploy and operate highly capable AI agents securely at scale, offering infrastructure purpose‑built for dynamic agent workloads, powerful tools to enhance agents, and essential controls for real‑world deployment. It works with any framework and any foundation model in or outside of Amazon Bedrock, eliminating the undifferentiated heavy lifting of specialized infrastructure. AgentCore provides complete session isolation and industry‑leading support for long‑running workloads up to eight hours, with native integration to existing identity providers for seamless authentication and permission delegation. A gateway transforms APIs into agent‑ready tools with minimal code, and built‑in memory maintains context across interactions. Agents gain a secure browser runtime for complex web‑based workflows and a sandboxed code interpreter for tasks like generating visualizations.Starting Price: $0.0895 per vCPU-hour -
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TimescaleDB
Tiger Data
TimescaleDB is the leading time-series database built on PostgreSQL, designed to handle massive volumes of real-time data efficiently. It enables organizations to store, analyze, and query time-series data — such as IoT sensor data, financial transactions, or event logs — using standard SQL. With hypertables, TimescaleDB automatically partitions data by time and ID for fast ingestion and predictable query performance. Its compression engine reduces storage costs by up to 95%, while continuous aggregates make real-time dashboards instantly responsive. Fully compatible with PostgreSQL, it integrates seamlessly with existing tools and applications. TimescaleDB combines the simplicity of Postgres with the scalability and speed of a specialized analytical system. -
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InfluxDB
InfluxData
InfluxDB is a purpose-built data platform designed to handle all time series data, from users, sensors, applications and infrastructure — seamlessly collecting, storing, visualizing, and turning insight into action. With a library of more than 250 open source Telegraf plugins, importing and monitoring data from any system is easy. InfluxDB empowers developers to build transformative IoT, monitoring and analytics services and applications. InfluxDB’s flexible architecture fits any implementation — whether in the cloud, at the edge or on-premises — and its versatility, accessibility and supporting tools (client libraries, APIs, etc.) make it easy for developers at any level to quickly build applications and services with time series data. Optimized for developer efficiency and productivity, the InfluxDB platform gives builders time to focus on the features and functionalities that give their internal projects value and their applications a competitive edge.Starting Price: $0 -
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Proficy Historian
GE Vernova
Proficy Historian is a best-in-class historian software solution that collects industrial time-series and A&E data at very high speed, stores it efficiently and securely, distributes it, and allows for fast retrieval and analysis —driving greater business value. With decades of experience and thousands of successful customer installations around the world, Proficy Historian changes the way companies perform and compete by making data available for asset and process performance analysis. The most recent Proficy Historian enhances usability, configurability and maintainability with significant architectural improvements. Take advantage of the solution’s simple yet powerful features to unlock new value from your equipment, process data, and business models. Remote collector management with UX. Horizontal scalability that enables enterprise-wide data visibility. -
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Amazon Elastic File System (Amazon EFS) automatically grows and shrinks as you add and remove files with no need for management or provisioning. Share code and other files in a secure, organized way to increase DevOps agility and respond faster to customer feedback. Persist and share data from your AWS containers and serverless applications with zero management required. Easier to use and scale, Amazon EFS offers the performance and consistency needed for machine learning and big data analytics workloads. Simplify persistent storage for modern content management system workloads. Get your products and services to market faster, more reliably, and securely at a lower cost. Create and configure shared file systems simply and quickly for AWS compute services, with no provisioning, deploying, patching, or maintenance required. Scale workloads on-demand to petabytes of storage and gigabytes per second of throughput out of the box.
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AWS AI Factories
Amazon
AWS AI Factories is a fully-managed solution that embeds high-performance AI infrastructure directly into a customer’s own data center. You supply the space and power, and AWS deploys a dedicated, secure AI environment optimized for training and inference. It includes leading AI accelerators (such as AWS Trainium chips or NVIDIA GPUs), low-latency networking, high-performance storage, and integration with AWS’s AI services, such as Amazon SageMaker and Amazon Bedrock, giving immediate access to foundational models and AI tools without separate licensing or contracts. AWS handles the full deployment, maintenance, and management, eliminating the typical months-long effort to build comparable infrastructure. Each deployment is isolated, operating like a private AWS Region, which meets strict data sovereignty, compliance, and regulatory requirements, making it particularly suited for sectors with sensitive data. -
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KX Streaming Analytics provides the ability to ingest, store, process, and analyze historic and time series data to make analytics, insights, and visualizations instantly available. To help ensure your applications and users are productive quickly, the platform provides the full lifecycle of data services, including query processing, tiering, migration, archiving, data protection, and scaling. Our advanced analytics and visualization tools, used widely across finance and industry, enable you to define and perform queries, calculations, aggregations, machine learning and AI on any streaming and historical data. Deployable across multiple hardware environments, data can come from real-time business events and high-volume sources including sensors, clickstreams, radio-frequency identification, GPS systems, social networking sites, and mobile devices.
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Easily store, share, and deploy your container software anywhere. Push container images to Amazon ECR without installing or scaling infrastructure, and pull images using any management tool. Share and download images securely over Hypertext Transfer Protocol Secure (HTTPS) with automatic encryption and access controls. Access and distribute your images faster, reduce download times, and improve availability using a scalable, durable architecture. Amazon ECR is a fully managed container registry offering high-performance hosting, so you can reliably deploy application images and artifacts anywhere. Meet your organization’s image compliance security requirements using insights from common vulnerabilities and exposures (CVEs) and the Common Vulnerability Scoring System (CVSS). Publish containerized applications with a single command and easily integrate your self-managed environments.
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Machbase
Machbase
Machbase, a time-series database that stores and analyzes a lot of sensor data from various facilities in real time, is the only DBMS solution that can process and analyze big data at high speed. Experience the amazing speed of Machbase! It is the most innovative product that enables real-time processing, storage, and analysis of sensor data. High speed sensor data storage and inquiry for sensor data by embedding DBMS in an Edge devices. Best data storage and extraction performance by DBMS running in a single server. Configuring Multi-node cluster with the advantages of availability and scalability. Total management solution of Edge computing for device, connectivity and data. -
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Amazon Augmented AI (A2I)
Amazon
Amazon Augmented AI (Amazon A2I) makes it easy to build the workflows required for human review of ML predictions. Amazon A2I brings human review to all developers, removing the undifferentiated heavy lifting associated with building human review systems or managing large numbers of human reviewers. Many machine learning applications require humans to review low confidence predictions to ensure the results are correct. For example, extracting information from scanned mortgage application forms can require human review in some cases due to low-quality scans or poor handwriting. But building human review systems can be time consuming and expensive because it involves implementing complex processes or “workflows”, writing custom software to manage review tasks and results, and in many cases, managing large groups of reviewers. -
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ITTIA DB
ITTIA
The ITTIA DB product family combines the best of time series, real-time data streaming, and analytics for embedded systems to reduce development time and costs. ITTIA DB IoT is a small-footprint embedded database for real-time resource-constrained 32-bit microcontrollers (MCUs), and ITTIA DB SQL is a high-performance time-series embedded database for single or multicore microprocessors (MPUs). Both ITTIA DB products enable devices to monitor, process, and store real-time data. ITTIA DB products are also built for the automotive industry Electronic Control Units (ECUs). ITTIA DB data security protocols offer data protection against malicious access with encryption, authentication, and DB SEAL. ITTIA SDL is conformant to the principles of IEC/ISO 62443. Embed ITTIA DB to collect, process, and enrich incoming real-time data streams in a purpose-built SDK for edge devices. Search, filter, join, and aggregate at the edge. -
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IBM Informix
IBM
IBM Informix® is a fast and flexible database with the ability to seamlessly integrate SQL, NoSQL/JSON, and time series and spatial data. Its versatility and ease of use make Informix a preferred solution for a wide range of environments, from enterprise data warehouses to individual application development. Also, with its small footprint and self-managing capabilities, Informix is well suited for embedded data-management solutions. IoT data demands robust processing and integration capabilities. Informix offers a hybrid database system with minimal administrative requirements and memory footprint combined with powerful functionality. Key features make Informix ideal for multi-tiered architectures that require processing at the device level, at gateway layers and in the cloud. Native encryption to protect data at rest and in motion. Support for flexible schema, multiple APIs and configurations. -
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JaguarDB
JaguarDB
JaguarDB enables fast ingestion of time series data, coupling location-based data. It also can index in both dimensions, space and time. Back-filling time series data is also fast (inserting large volumes of data in past time). Normally time series is a series of data points indexed in time order. In JaguarDB, the time series has a different meaning: it is both a sequence of data points and a series of tick tables holding aggregated data values at specified time spans. For example, a time series table in JaguarDB can have a base table storing data points in time order, and tick tables such as 5 minute, 15 minute, hourly, daily, weekly, monthly tables to store aggregated data within these time spans. The format for the RETENTION is the same as the TICK format, except that it can have any number of retention periods. The RETENTION specifies how long the data points in the base table should be kept. -
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Google Cloud Bigtable
Google
Google Cloud Bigtable is a fully managed, scalable NoSQL database service for large analytical and operational workloads. Fast and performant: Use Cloud Bigtable as the storage engine that grows with you from your first gigabyte to petabyte-scale for low-latency applications as well as high-throughput data processing and analytics. Seamless scaling and replication: Start with a single node per cluster, and seamlessly scale to hundreds of nodes dynamically supporting peak demand. Replication also adds high availability and workload isolation for live serving apps. Simple and integrated: Fully managed service that integrates easily with big data tools like Hadoop, Dataflow, and Dataproc. Plus, support for the open source HBase API standard makes it easy for development teams to get started. -
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ArcadeDB
ArcadeDB
ArcadeDB is an open-source, next-generation multi-model database. Forget Polyglot Persistence — store graphs, documents, key-value pairs, search engine indexes, vectors, and time-series data all in one database with native support for every model. No translation layers, no performance penalties. Process over 10 million records per second. Traversal speed stays constant whether your database has hundreds or billions of records. Query in the language you prefer: SQL, Cypher, Gremlin, GraphQL, MongoDB API, or Java. Deploy ArcadeDB embedded in your JVM application, on a standalone server, or distributed across multiple nodes with Raft Consensus for high availability. Fully ACID-compliant. Super lightweight. Apache 2.0 licensed — free for production and commercial use.Starting Price: Free -
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Amazon Keyspaces
Amazon
Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra–compatible database service. With Amazon Keyspaces, you can run your Cassandra workloads on AWS using the same Cassandra application code and developer tools that you use today. You don’t have to provision, patch, or manage servers, and you don’t have to install, maintain, or operate software. Amazon Keyspaces is serverless, so you pay for only the resources you use and the service can automatically scale tables up and down in response to application traffic. You can build applications that serve thousands of requests per second with virtually unlimited throughput and storage. Amazon Keyspaces gives you the performance, elasticity, and enterprise features you need to operate business-critical Cassandra workloads at scale. Process data at high speeds for applications that require single-digit-millisecond latency, such as industrial equipment maintenance, trade monitoring, etc. -
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Amazon Registry
Amazon
Amazon Registry Services, Inc. brings Amazon’s customer-obsession to the domain space by creating intuitive and vibrant Internet solutions for customers and partners. Our goal is to create new spaces that will help customers and partners evolve with the ever changing Internet environment. Each domain space offers key services for its customers and end users that will grow over time. We are investing in the next evolution of the Internet that will drive new customer segments to the domain space, and we are looking to partner with innovative registrars to join us on our journey. Pioneer with us to deliver unique experiences and increase your global market reach. -
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BaseSpace Sequence Hub
Illumina
Data management and simplified bioinformatics for labs getting started and for rapidly scaling next-generation sequencing (NGS) operations. As a key component of the BaseSpace Suite, BaseSpace Sequence Hub is a direct extension of your Illumina instruments. Encrypted data flow from the instrument into BaseSpace Sequence Hub, enabling you to manage and analyze your data easily with a curated set of analysis apps. BaseSpace Sequence Hub is powered by Amazon Web Services (AWS). Offers a security-first environment. Enables you to set up runs and monitor instrument run quality. Promotes efficiency by converting sequencing data to a standard format and streaming directly to the cloud. Provides access to computing resources without the capital expenditure of in-house infrastructure. Increases organizational productivity with easy access to a multitude of genomic analysis apps (provided by you, Illumina, or third parties). -
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Blueflood
Blueflood
Blueflood is a high throughput, low latency, multi-tenant distributed metric processing system behind Rackspace Metrics, which is currently used in production by the Rackspace Monitoring team and Rackspace public cloud team to store metrics generated by their systems. In addition to Rackspace metrics, other large scale deployments of Blueflood can be found at community Wiki. Data from Blueflood can be used to construct dashboards, generate reports, graphs or for any other use involving time-series data. It focuses on near-realtime data, with data that is queryable mere milliseconds after ingestion. You send metrics to the ingestion service. You query your metrics from the Query service. And in the background, rollups are batch-processed offline so that queries for large time-periods are returned quickly. -
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Amazon Managed Grafana
Amazon
Amazon Managed Grafana is a fully managed service that simplifies the process of visualizing and analyzing operational data at scale. It allows users to create workspaces, logically isolated Grafana servers, that can be provisioned, set up, scaled and maintained automatically. These workspaces enable the visualization, analysis, and correlation of operational data across multiple sources, including AWS services like Amazon CloudWatch, AWS X-Ray, and Amazon Managed Service for Prometheus, as well as third-party data sources. It integrates seamlessly with AWS security services, ensuring compliance with corporate security requirements. Additionally, Amazon Managed Grafana supports migration from self-managed Grafana environments, allowing users to retain existing dashboards and configurations. It also offers collaborative features such as real-time dashboard viewing and editing, version tracking, and sharing capabilities, enhancing team productivity. -
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VictoriaMetrics
VictoriaMetrics
VictoriaMetrics is a fast and scalable open source time series database and monitoring solution. It's designed to be user-friendly, allowing users to build a monitoring platform without scalability issues and with minimal operational burden. VictoriaMetrics is ideal for solving use cases with large amounts of time series data for IT infrastructure, APM, Kubernetes, IoT sensors, automotive vehicles, industrial telemetry, financial data, and other enterprise-level workloads. VictoriaMetrics is powered by several components, making it the perfect solution for collecting metrics (both push and pull models), running queries, and generating alerts. With VictoriaMetrics, you can store millions of data points per second on a single instance or scale to a high-load monitoring system across multiple data centers. Plus, it's designed to store 10x more data using the same compute and storage resources as existing solutions, making it a highly efficient choice.Starting Price: $0 -
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AWS CloudFormation
Amazon
AWS CloudFormation is a infrastructure provisioning and management tool that provides you the ability to create resource templates that specifies a set of AWS resources to provision. The templates allow you to version control your infrastructure, and also easily replicate your infrastructure stack quickly and with repeatability. Define an Amazon Virtual Private Cloud (VPC) subnet or provisioning services like AWS OpsWorks or Amazon Elastic Container Service (ECS) with ease. Run anything from a single Amazon Elastic Compute Cloud (EC2) instance to a complex multi-region application. Automate, test, and deploy infrastructure templates with continuous integration and delivery (CI/CD) automation. AWS CloudFormation lets you model, provision, and manage AWS and third-party resources by treating infrastructure as code. Speed up cloud provisioning with infrastructure as code.Starting Price: $0.0009 per handler operation -
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AWS Directory Service
Amazon
AWS Directory Service for Microsoft Active Directory, also known as AWS Managed Microsoft Active Directory (AD), enables your directory-aware workloads and AWS resources to use managed Active Directory (AD) in AWS. AWS Managed Microsoft AD is built on actual Microsoft AD and does not require you to synchronize or replicate data from your existing Active Directory to the cloud. You can use the standard AD administration tools and take advantage of the built-in AD features, such as Group Policy and single sign-on. With AWS Managed Microsoft AD, you can easily join Amazon EC2 and Amazon RDS for SQL Server instances to your domain, and use AWS End User Computing (EUC) services, such as Amazon WorkSpaces, with AD users and groups. AWS Managed Microsoft AD makes it easy to migrate AD-dependent applications and Windows workloads to AWS. With AWS Managed Microsoft AD, you can use Group Policies to manage EC2 instances and run AD-dependent applications in the AWS Cloud.Starting Price: $0.018 -
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Amazon Bedrock
Amazon
Amazon Bedrock is a fully managed service that simplifies building and scaling generative AI applications by providing access to a variety of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself. Through a single API, developers can experiment with these models, customize them using techniques like fine-tuning and Retrieval Augmented Generation (RAG), and create agents that interact with enterprise systems and data sources. As a serverless platform, Amazon Bedrock eliminates the need for infrastructure management, allowing seamless integration of generative AI capabilities into applications with a focus on security, privacy, and responsible AI practices. -
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AWS IoT Core
Amazon
AWS IoT Core lets you connect IoT devices to the AWS cloud without the need to provision or manage servers. AWS IoT Core can support billions of devices and trillions of messages, and can process and route those messages to AWS endpoints and to other devices reliably and securely. With AWS IoT Core, your applications can keep track of and communicate with all your devices, all the time, even when they aren’t connected. AWS IoT Core also makes it easy to use AWS and Amazon services like AWS Lambda, Amazon Kinesis, Amazon S3, Amazon SageMaker, Amazon DynamoDB, Amazon CloudWatch, AWS CloudTrail, Amazon QuickSight, and Alexa Voice Service to build IoT applications that gather, process, analyze and act on data generated by connected devices, without having to manage any infrastructure. AWS IoT Core allows you to connect any number of devices to the cloud and to other devices without requiring you to provision or manage servers. -
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Axibase Time Series Database
Axibase
Parallel query engine with time- and symbol-indexed data access. Extended SQL syntax with advanced filtering and aggregations. Consolidate quotes, trades, snapshots, and reference data in one place. Strategy backtesting on high-frequency data. Quantitative and market microstructure research. Granular transaction cost analysis and rollup reporting. Market surveillance and anomaly detection. Non-transparent ETF/ETN decomposition. FAST, SBE, and proprietary protocols. Plain text protocol. Consolidated and direct feeds. Built-in latency monitoring tools. End-of-day archives. ETL from institutional and retail financial data platforms. Parallel SQL engine with syntax extensions. Advanced filtering by trading session, auction stage, index composition. Optimized aggregates for OHLCV and VWAP calculations. Interactive SQL console with auto-completion. API endpoint for programmatic integration. Scheduled SQL reporting with email, file, and web delivery. JDBC and ODBC drivers. -
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Scanner
Scanner
Scanner.dev is a cloud-native security data lake and lightweight security information and event management (SIEM) platform that indexes logs directly in your own Amazon S3 buckets, letting you retain unlimited logs and run full-text searches across petabytes of data in seconds without additional ETL or schema requirements. It builds lightweight indexes that make any log format instantly searchable and supports hyper-fast search and investigation, continuous threat detection with customizable detection rules managed as code via GitHub, and integrated alerting with APIs for automation and integration into existing security workflows. Scanner’s streaming detection engine continuously evaluates rule queries in near real time and can backtest detection logic against historical data, while its API and Model Context Protocol (MCP) enable programmatic access and AI-assisted analysis of security data.Starting Price: $30,000 per year -
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Amazon Kinesis
Amazon
Easily collect, process, and analyze video and data streams in real time. Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin. Amazon Kinesis enables you to ingest, buffer, and process streaming data in real-time, so you can derive insights in seconds or minutes instead of hours or days. -
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Amazon SimpleDB
Amazon
Amazon SimpleDB is a highly available NoSQL data store that offloads the work of database administration. Developers simply store and query data items via web services requests and Amazon SimpleDB does the rest. Unbound by the strict requirements of a relational database, Amazon SimpleDB is optimized to provide high availability and flexibility, with little or no administrative burden. Behind the scenes, Amazon SimpleDB creates and manages multiple geographically distributed replicas of your data automatically to enable high availability and data durability. The service charges you only for the resources actually consumed in storing your data and serving your requests. You can change your data model on the fly, and data is automatically indexed for you. With Amazon SimpleDB, you can focus on application development without worrying about infrastructure provisioning, high availability, software maintenance, schema and index management, or performance tuning. -
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QCT QuantaPlex
QCT
The QCT QuantaPlex series is a sophisticated line of multi-node servers that deliver exceptionally high density and computing performance, making them ideal for data-intensive applications. Designed with a shared infrastructure approach, the QuantaPlex series offers the flexibility to accommodate various workloads, including large-scale data computing, data storage, and business-critical applications. By maximizing space utilization and optimizing cooling and energy efficiency, the QuantaPlex series effectively reduces total cost of ownership (TCO) while providing organizations with a powerful and versatile solution for meeting their data center and computing needs. -
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Warp 10
SenX
Warp 10 is a modular open source platform that collects, stores, and analyzes data from sensors. Shaped for the IoT with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 is both a time series database and a powerful analytics environment, allowing you to make: statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The analysis environment can be implemented within a large ecosystem of software components such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. It can also access data stored in many existing solutions, relational or NoSQL databases, search engines and S3 type object storage system. -
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PartyRock
Amazon
PartyRock is a space where you can build AI-generated apps in a playground powered by Amazon Bedrock. It’s a fast and fun way to learn about generative AI. PartyRock, launched by Amazon Web Services (AWS) in November 2023, is a user-friendly platform that enables users to create generative AI-powered applications without any coding experience. By simply describing the desired app, users can build a variety of applications, from simple text generators to sophisticated productivity tools that combine multiple AI capabilities. Since its inception, over half a million apps have been built by users worldwide. artyRock operates as a playground powered by Amazon Bedrock, AWS's fully managed service that provides access to foundational AI models. The platform offers a web-based interface, eliminating the need for an AWS account, and allows users to sign in with their existing social credentials. Users can explore hundreds of thousands of published apps, categorized by functionality. -
47
Amazon FSx
Amazon
Amazon FSx makes it easy and cost effective to launch, run, and scale feature-rich, high-performance file systems in the cloud. It supports a wide range of workloads with its reliability, security, scalability, and broad set of capabilities. Amazon FSx is built on the latest AWS compute, networking, and disk technologies to provide high performance and lower TCO. And as a fully managed service, it handles hardware provisioning, patching, and backups -- freeing you up to focus on your applications, your end users, and your business. -
48
QuestDB
QuestDB
QuestDB is a relational column-oriented database designed for time series and event data. It uses SQL with extensions for time series to assist with real-time analytics. These pages cover core concepts of QuestDB, including setup steps, usage guides, and reference documentation for syntax, APIs and configuration. This section describes the architecture of QuestDB, how it stores and queries data, and introduces features and capabilities unique to the system. Designated timestamp is a core feature that enables time-oriented language capabilities and partitioning. Symbol type makes storing and retrieving repetitive strings efficient. Storage model describes how QuestDB stores records and partitions within tables. Indexes can be used for faster read access on specific columns. Partitions can be used for significant performance benefits on calculations and queries. SQL extensions allow performant time series analysis with a concise syntax. -
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AWS Snowball
Amazon
Accelerate moving offline data or remote storage to the cloud. Easily migrate petabytes of data to the cloud without limits in storage capacity or compute power. Accelerate application performance in disconnected, austere edge environments and run compute workloads with little or no connectivity. Protect your data in transit with Snowball’s ruggedized chassis, integrated logistics, and tamper-evident box, and get data to the right place quickly. In the AWS Snowball console, select your preferred device, either AWS Snowball Edge Compute Optimized or AWS Snowball Edge Storage Optimized. Create a job with an Amazon S3 bucket, select Amazon Simple Notification Service (Amazon SNS) for tracking, and configure options like Amazon EC2 AMIs. AWS prepares and ships the device to you. Once the device arrives, power it up and use AWS OpsHub to unlock it. Connect to your LAN. Use AWS OpsHub to manage the device, transfer data, or launch EC2 instances. -
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Amazon Fraud Detector
Amazon
Build, deploy, and manage fraud detection models without previous machine learning (ML) experience. Gain insights from your historical data, plus 20+ years of Amazon experience, to construct an accurate, customized fraud detection model. Start detecting fraud immediately, easily enhance models with customized business rules, and deploy results to generate critical predictions. Build, deploy, and manage fraud detection models without previous machine learning (ML) experience. Gain insights from your historical data, plus 20+ years of Amazon experience, to construct an accurate, customized fraud detection model. Start detecting fraud immediately, easily enhance models with customized business rules, and deploy results to generate critical predictions. Amazon Fraud Detector is a fully managed service enabling customers to identify potentially fraudulent activities and catch more online fraud faster.
