Alternatives to Exasol
Compare Exasol alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Exasol in 2026. Compare features, ratings, user reviews, pricing, and more from Exasol competitors and alternatives in order to make an informed decision for your business.
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Teradata VantageCloud
Teradata
Teradata VantageCloud: The complete cloud analytics and data platform for AI. Teradata VantageCloud is an enterprise-grade, cloud-native data and analytics platform that unifies data management, advanced analytics, and AI/ML capabilities in a single environment. Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It offers full ANSI SQL support, integrates with open-source tools like Python and R, and provides built-in governance for secure, trusted AI. VantageCloud empowers users to run complex queries, build data pipelines, and operationalize machine learning models—all while maintaining interoperability with modern data ecosystems. -
2
Google Cloud BigQuery
Google
BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process. -
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Dragonfly
DragonflyDB
Dragonfly is a drop-in Redis replacement that cuts costs and boosts performance. Designed to fully utilize the power of modern cloud hardware and deliver on the data demands of modern applications, Dragonfly frees developers from the limits of traditional in-memory data stores. The power of modern cloud hardware can never be realized with legacy software. Dragonfly is optimized for modern cloud computing, delivering 25x more throughput and 12x lower snapshotting latency when compared to legacy in-memory data stores like Redis, making it easy to deliver the real-time experience your customers expect. Scaling Redis workloads is expensive due to their inefficient, single-threaded model. Dragonfly is far more compute and memory efficient, resulting in up to 80% lower infrastructure costs. Dragonfly scales vertically first, only requiring clustering at an extremely high scale. This results in a far simpler operational model and a more reliable system. -
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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. -
5
StarTree
StarTree
StarTree, powered by Apache Pinot™, is a fully managed real-time analytics platform built for customer-facing applications that demand instant insights on the freshest data. Unlike traditional data warehouses or OLTP databases—optimized for back-office reporting or transactions—StarTree is engineered for real-time OLAP at true scale, meaning: - Data Volume: query performance sustained at petabyte scale - Ingest Rates: millions of events per second, continuously indexed for freshness - Concurrency: thousands to millions of simultaneous users served with sub-second latency With StarTree, businesses deliver always-fresh insights at interactive speed, enabling applications that personalize, monitor, and act in real time.Starting Price: Free -
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SAP HANA Cloud
SAP
SAP HANA Cloud is a fully managed in-memory cloud database as a service (DBaaS). As the cloud-based data foundation for SAP Business Technology Platform, it integrates data from across the enterprise, enabling faster decisions based on live data. Build data solutions with modern architectures and gain business-ready insights in real-time. As the data foundation for SAP Business Technology Platform, the SAP HANA Cloud database offers the power of SAP HANA in the cloud. Scale to your needs, process business data of all types, and perform advanced analytics on live transactions without tuning for fast, improved decision-making. Connect to distributed data with native integration, develop applications and tools across clouds and on-premise, and store volatile data. Tap business-ready information by creating one source of truth and enable security, privacy, and anonymization with enterprise reliability. -
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Amazon ElastiCache
Amazon
Amazon ElastiCache allows you to seamlessly set up, run, and scale popular open-Source compatible in-memory data stores in the cloud. Build data-intensive apps or boost the performance of your existing databases by retrieving data from high throughput and low latency in-memory data stores. Amazon ElastiCache is a popular choice for real-time use cases like Caching, Session Stores, Gaming, Geospatial Services, Real-Time Analytics, and Queuing. Amazon ElastiCache offers fully managed Redis and Memcached for your most demanding applications that require sub-millisecond response times. Amazon ElastiCache works as an in-memory data store and cache to support the most demanding applications requiring sub-millisecond response times. By utilizing an end-to-end optimized stack running on customer-dedicated nodes, Amazon ElastiCache provides secure, blazing-fast performance. -
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Redis
Redis Labs
Redis Labs: home of Redis. Redis Enterprise is the best version of Redis. Go beyond cache; try Redis Enterprise free in the cloud using NoSQL & data caching with the world’s fastest in-memory database. Run Redis at scale, enterprise grade resiliency, massive scalability, ease of management, and operational simplicity. DevOps love Redis in the Cloud. Developers can access enhanced data structures, a variety of modules, and rapid innovation with faster time to market. CIOs love the confidence of working with 99.999% uptime best in class security and expert support from the creators of Redis. Implement relational databases, active-active, geo-distribution, built in conflict distribution for simple and complex data types, & reads/writes in multiple geo regions to the same data set. Redis Enterprise offers flexible deployment options, cloud on-prem, & hybrid. Redis Labs: home of Redis. Redis JSON, Redis Java, Python Redis, Redis on Kubernetes & Redis gui best practices.Starting Price: Free -
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SAP HANA
SAP
SAP HANA in-memory database is for transactional and analytical workloads with any data type — on a single data copy. It breaks down the transactional and analytical silos in organizations, for quick decision-making, on premise and in the cloud. Innovate without boundaries on a database management system, where you can develop intelligent and live solutions for quick decision-making on a single data copy. And with advanced analytics, you can support next-generation transactional processing. Build data solutions with cloud-native scalability, speed, and performance. With the SAP HANA Cloud database, you can gain trusted, business-ready information from a single solution, while enabling security, privacy, and anonymization with proven enterprise reliability. An intelligent enterprise runs on insight from data – and more than ever, this insight must be delivered in real time. -
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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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eXtremeDB
McObject
How is platform independent eXtremeDB different? - Hybrid data storage. Unlike other IMDS, eXtremeDB can be all-in-memory, all-persistent, or have a mix of in-memory tables and persistent tables - Active Replication Fabric™ is unique to eXtremeDB, offering bidirectional replication, multi-tier replication (e.g. edge-to-gateway-to-gateway-to-cloud), compression to maximize limited bandwidth networks and more - Row & Columnar Flexibility for Time Series Data supports database designs that combine row-based and column-based layouts, in order to best leverage the CPU cache speed - Embedded and Client/Server. Fast, flexible eXtremeDB is data management wherever you need it, and can be deployed as an embedded database system, and/or as a client/server database system -A hard real-time deterministic option in eXtremeDB/rt Designed for use in resource-constrained, mission-critical embedded systems. Found in everything from routers to satellites to trains to stock markets worldwide -
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Apache Ignite
Apache Ignite
Use Ignite as a traditional SQL database by leveraging JDBC drivers, ODBC drivers, or the native SQL APIs that are available for Java, C#, C++, Python, and other programming languages. Seamlessly join, group, aggregate, and order your distributed in-memory and on-disk data. Accelerate your existing applications by 100x using Ignite as an in-memory cache or in-memory data grid that is deployed over one or more external databases. Think of a cache that you can query with SQL, transact, and compute on. Build modern applications that support transactional and analytical workloads by using Ignite as a database that scales beyond the available memory capacity. Ignite allocates memory for your hot data and goes to disk whenever applications query cold records. Execute kilobyte-size custom code over petabytes of data. Turn your Ignite database into a distributed supercomputer for low-latency calculations, complex analytics, and machine learning. -
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Hazelcast
Hazelcast
In-Memory Computing Platform. The digital world is different. Microseconds matter. That's why the world's largest organizations rely on us to power their most time-sensitive applications at scale. New data-enabled applications can deliver transformative business power – if they meet today’s requirement of immediacy. Hazelcast solutions complement virtually any database to deliver results that are significantly faster than a traditional system of record. Hazelcast’s distributed architecture provides redundancy for continuous cluster up-time and always available data to serve the most demanding applications. Capacity grows elastically with demand, without compromising performance or availability. The fastest in-memory data grid, combined with third-generation high-speed event processing, delivered through the cloud. -
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Oracle TimesTen
Oracle
Oracle TimesTen In-Memory Database (TimesTen) delivers real time application performance (low response time and high throughput) by changing the assumptions around where data resides at runtime. By managing data in memory, and optimizing data structures and access algorithms accordingly, database operations execute with maximum efficiency achieving dramatic gains in responsiveness and throughput. With the introduction of TimesTen Scaleout, a shared nothing scale-out architecture based on the existing in-memory technology, TimesTen allows databases to transparently scale across dozens of hosts, reach hundreds of terabytes in size and support hundreds of millions of transactions per second without the need for manual database sharding or workload partitioning. -
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GridDB
GridDB
GridDB uses multicast communication to constitute a cluster. Set the network to enable multicast communication. First, check the host name and an IP address. Execute “hostname -i” command to check the settings of an IP address of the host. If the IP address of the machine is the same as below, no need to perform additional network setting and you can jump to the next section. GridDB is a database that manages a group of data (known as a row) that is made up of a key and multiple values. Besides having a composition of an in-memory database that arranges all the data in the memory, it can also adopt a hybrid composition combining the use of a disk (including SSD as well) and a memory. -
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SingleStore
SingleStore
SingleStore (formerly MemSQL) is a distributed, highly-scalable SQL database that can run anywhere. We deliver maximum performance for transactional and analytical workloads with familiar relational models. SingleStore is a scalable SQL database that ingests data continuously to perform operational analytics for the front lines of your business. Ingest millions of events per second with ACID transactions while simultaneously analyzing billions of rows of data in relational SQL, JSON, geospatial, and full-text search formats. SingleStore delivers ultimate data ingestion performance at scale and supports built in batch loading and real time data pipelines. SingleStore lets you achieve ultra fast query response across both live and historical data using familiar ANSI SQL. Perform ad hoc analysis with business intelligence tools, run machine learning algorithms for real-time scoring, perform geoanalytic queries in real time.Starting Price: $0.69 per hour -
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Apache Doris
The Apache Software Foundation
Apache Doris is a modern data warehouse for real-time analytics. It delivers lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation. Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine. Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL. Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches. Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.Starting Price: Free -
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Citus
Citus Data
Citus gives you the Postgres you love, plus the superpower of distributed tables. 100% open source. Now with schema-based and row-based sharding, plus Postgres 16 support. Scale Postgres by distributing data & queries. You can start with a single Citus node, then add nodes & rebalance shards when you need to grow. Speed up queries by 20x to 300x (or more) through parallelism, keeping more data in memory, higher I/O bandwidth, and columnar compression. Citus is an extension (not a fork) to the latest Postgres versions, so you can use your familiar SQL toolset & leverage your Postgres expertise. Reduce your infrastructure headaches by using a single database for both your transactional and analytical workloads. Download and use Citus open source for free. You can manage Citus yourself, embrace open source, and help us improve Citus via GitHub. Focus on your application & forget about your database. Run your app on Citus in the cloud with Azure Cosmos DB for PostgreSQL.Starting Price: $0.27 per hour -
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Starcounter
Starcounter
Our ACID in-memory technology and application server enable you to build lightning-fast enterprise software. Without custom tooling or new syntax. Starcounter applications let you achieve 50 to 1000 times better performance without adding complexity. Applications are written in regular C#, LINQ, and SQL. Even the ACID transactions are written in regular C# code. Full Visual Studio support including IntelliSense, debugger, and performance profiler. All the things you like, minus the headache. Write regular C# syntax with MVVM pattern to leverage ACID in-memory technology and thin client UI for extreme performance. Starcounter technology adds business value from day one. We leverage technology that’s already developed and in production, processing millions of business transactions for high-demand customers. Starcounter combines ACID in-memory database and application server into a single platform unmatched in performance, simplicity, and price.Starting Price: Free -
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FairCom DB
FairCom Corporation
FairCom DB is ideal for large-scale, mission-critical, core-business applications that require performance, reliability and scalability that cannot be achieved by other databases. FairCom DB delivers predictable high-velocity transactions and massively parallel big data analytics. It empowers developers with NoSQL APIs for processing binary data at machine speed and ANSI SQL for easy queries and analytics over the same binary data. Among the companies that take advantage of the flexibility of FairCom DB is Verizon, who recently chose FairCom DB as an in-memory database for its Verizon Intelligent Network Control Platform Transaction Server Migration. FairCom DB is an advanced database engine that gives you a Continuum of Control to achieve unprecedented performance with the lowest total cost of ownership (TCO). You do not conform to FairCom DB…FairCom DB conforms to you. With FairCom DB, you are not forced to conform your needs to meet the limitations of the database. -
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Infobright DB
IgniteTech
Infobright DB is a high-performance enterprise database leveraging a columnar storage engine to enable business analysts to dissect data efficiently and more quickly obtain reports. InfoBright DB can be deployed on-premise or in the cloud. Store & analyze big data for interactive business intelligence and complex queries. Improve query performance, reduce storage cost and increase overall efficiency in business analytics and reporting. Easily store up to several hundred TB of data — traditionally not achievable with conventional databases. Run big data applications and eliminate indexing and partitioning — with zero administrative overhead. With the volumes of machine data exploding, IgniteTech’s Infobright DB is specifically designed to achieve high performance for large volumes of machine-generated data. Manage a complex ad hoc analytic environments without the database administration required by other products. -
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Hydra
Hydra
Hydra is an open source, column-oriented Postgres. Query billions of rows instantly, no code changes. Hydra parallelizes and vectorizes aggregates (COUNT, SUM, AVG) to deliver the speed you’ve always wanted on Postgres. Boost performance at every size! Set up Hydra in 5 minutes without changing your syntax, tools, data model, or extensions. Use Hydra Cloud for fully managed operations and smooth sailing. Different industries have different needs. Get better analytics with powerful Postgres extensions, custom functions, and take control. Built by you, for you. Hydra is the fastest Postgres in the market for analytics. Boost performance with columnar storage, vectorization, and query parallelization. -
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VMware Tanzu GemFire
Broadcom
VMware Tanzu GemFire is a distributed, in-memory, key-value store that performs read and write operations at blazingly fast speeds. It offers highly available parallel message queues, continuous availability, and an event-driven architecture you can scale dynamically, with no downtime. As your data size requirements increase to support high-performance, real-time apps, Tanzu GemFire can scale linearly with ease. Traditional databases are often too brittle or unreliable for use with microservices. That’s why every modern distributed architecture needs a cache! With Tanzu GemFire, applications get low-latency responses to data access requests, and always return fresh data. Your applications can subscribe to real-time events to react to changes immediately. Tanzu GemFire’s continuous queries notify your application when new data is available, which reduces the overhead on your SQL database. -
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Apache Geode
Apache
Build high-speed, data-intensive applications that elastically meet performance requirements at any scale. Take advantage of Apache Geode's unique technology that blends advanced techniques for data replication, partitioning and distributed processing. Apache Geode provides a database-like consistency model, reliable transaction processing and a shared-nothing architecture to maintain very low latency performance with high concurrency processing. Data can easily be partitioned (sharded) or replicated between nodes allowing performance to scale as needed. Durability is ensured through redundant in-memory copies and disk-based persistence. Super fast write-ahead-logging (WAL) persistence with a shared-nothing architecture that is optimized for fast parallel recovery of nodes or an entire cluster. -
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Symas LMDB
Symas Corporation
Symas LMDB is an extraordinarily fast, memory-efficient database we developed for the OpenLDAP Project. With memory-mapped files, it has the read performance of a pure in-memory database while retaining the persistence of standard disk-based databases. Bottom line, with only 32KB of object code, LMDB may seem tiny. But it’s the right 32KB. Compact and efficient are two sides of a coin; that’s part of what makes LMDB so powerful. Symas offers fixed-price commercial support to those using LMDB in your applications. Development occurs in the OpenLDAP Project‘s git repo in the mdb.master branch. Symas LMDB has been written about, talked about, and utilized in a variety of impressive products and publications. -
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Terracotta
Software AG
Terracotta DB is a comprehensive, distributed in-memory data management solution which caters to caching and operational storage use cases, and enables transactional and analytical processing. Ultra-Fast Ram + Big Data = Business Power. With BigMemory, you get: Real-time access to terabytes of in-memory data. High throughput with low, predictable latency. Support for Java®, Microsoft® .NET/C#, C++ applications. 99.999 percent uptime. Linear scalability. Data consistency guarantees across multiple servers. Optimized data storage across RAM and SSD. SQL support for querying in-memory data. Reduced infrastructure costs through maximum hardware utilization. High-performance, persistent storage for durability and ultra-fast restart. Advanced monitoring, management and control. Ultra-fast in-memory data stores that automatically move data where it’s needed. Support for data replication across multiple data centers for disaster recovery. Manage fast-moving data in real time -
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Apache Arrow
The Apache Software Foundation
Apache Arrow defines a language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware like CPUs and GPUs. The Arrow memory format also supports zero-copy reads for lightning-fast data access without serialization overhead. Arrow's libraries implement the format and provide building blocks for a range of use cases, including high performance analytics. Many popular projects use Arrow to ship columnar data efficiently or as the basis for analytic engines. Apache Arrow is software created by and for the developer community. We are dedicated to open, kind communication and consensus decisionmaking. Our committers come from a range of organizations and backgrounds, and we welcome all to participate with us. -
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Amazon MemoryDB
Amazon
Valkey- and Redis OSS-compatible, durable, in-memory database service for ultra-fast performance. Scale to hundreds of millions of requests per second and over one hundred terabytes of storage per cluster. Stores data durably using a multi-AZ transaction log for 99.99% availability and near-instantaneous recovery without data loss. Secure your data with encryption at rest and in transit, private VPC endpoints, and multiple authentication mechanisms, including IAM authentication. Quickly build applications with Valkey and Redis OSS data structures and a rich open source API, and easily integrate with other AWS services. Deliver real-time personalized experiences with the highest relevancy and fastest semantic search experience among popular vector databases on AWS. Simplify application development and improve time-to-market with built-in access to flexible data structures that are available in Valkey and Redis OSS.Starting Price: $0.2163 per hour -
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PowerOLAP
PARIS Technologies International
Tap into timely and accurate data available across your organization, synchronized and delivered in real-time to the right people. Access through Excel, live information from your organization’s data sources, which have been connected through PowerOLAP’s in-memory database. Significantly reduce current reporting time and effort, and see dramatic increases in staff productivity. Enable faster budgeting cycles, dynamic report building, and advanced analytics through “multidimensional” views of your company’s business structure and performance. Ability to unite disparate systems for aggregated data from all key sources. Agility to collaborate team-wide on updated data and analytics with a simple refresh. Power and business intelligence analytics to make data-informed decisions. -
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BigObject
BigObject
At the heart of our innovation is in-data computing, a technology designed to process large amounts of data efficiently. Our flagship product, BigObject, embodies this core technology; it’s a time series database developed with the goal of high-speed storage and handling of massive data. With our core technology of in-data computing, we launched BigObject, which can quickly and continuously handle non-stop and all aspects of data streams. BigObject is a time series database developed with the goal of high-speed storage and analysis of massive data. It boasts excellent performance and powerful complex query capabilities. Extending the relational data structure to a time-series model structure, it utilizes in-data computing to optimize the database’s performance. Our core technology is an abstract model in which all data is kept in an infinite and persistent memory space for both storage and computing. -
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Lenovo ThinkAgile HX Series
Lenovo
Designed for easy deployment and manageability, Lenovo ThinkAgile HX combines Nutanix software with Lenovo's #1 reliable, high performing platforms. The ThinkAgile HX1021 certified node is a purpose-built Edge solution with right-sized compute and storage on a 1U height, half-width, and short-depth form factor meeting customer needs at remote locations. The condensed design of the solution allows new compute possibilities directly where data is being generated such as a retail, manufacturing units, gas stations, restaurants, healthcare, and education. Now enhanced with new second-generation Intel processors for even faster performance, the ThinkAgile HX portfolio is optimized for a broad set of virtualized workloads, including Remote Office Branch Office; file, print, and email applications; analytics; and in-memory databases. Lenovo platforms hold the highest number of performance world records and have ranked #1 in reliability for six consecutive years. -
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Trino
Trino
Trino is a query engine that runs at ludicrous speed. Fast-distributed SQL query engine for big data analytics that helps you explore your data universe. Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low-latency analytics. The largest organizations in the world use Trino to query exabyte-scale data lakes and massive data warehouses alike. Supports diverse use cases, ad-hoc analytics at interactive speeds, massive multi-hour batch queries, and high-volume apps that perform sub-second queries. Trino is an ANSI SQL-compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset, and many others. You can natively query data in Hadoop, S3, Cassandra, MySQL, and many others, without the need for complex, slow, and error-prone processes for copying the data. Access data from multiple systems within a single query.Starting Price: Free -
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H2
H2
Welcome to H2, the Java SQL database. In embedded mode, an application opens a database from within the same JVM using JDBC. This is the fastest and easiest connection mode. The disadvantage is that a database may only be open in one virtual machine (and class loader) at any time. As in all modes, both persistent and in-memory databases are supported. There is no limit on the number of database open concurrently, or on the number of open connections. The mixed mode is a combination of the embedded and the server mode. The first application that connects to a database does that in embedded mode, but also starts a server so that other applications (running in different processes or virtual machines) can concurrently access the same data. The local connections are as fast as if the database is used in just the embedded mode, while the remote connections are a bit slower. -
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OpenText Analytics Database is a high-performance, scalable analytics platform that enables organizations to analyze massive data sets quickly and cost-effectively. It supports real-time analytics and in-database machine learning to deliver actionable business insights. The platform can be deployed flexibly across hybrid, multi-cloud, and on-premises environments to optimize infrastructure and reduce total cost of ownership. Its massively parallel processing (MPP) architecture handles complex queries efficiently, regardless of data size. OpenText Analytics Database also features compatibility with data lakehouse architectures, supporting formats like Parquet and ORC. With built-in machine learning and broad language support, it empowers users from SQL experts to Python developers to derive predictive insights.
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GridGain
GridGain Systems
The enterprise-grade platform built on Apache Ignite that provides in-memory speed and massive scalability for data-intensive applications and real-time data access across datastores and applications. Upgrade from Ignite to GridGain with no code changes and deploy your clusters securely at global scale with zero downtime. Perform rolling upgrades of your production clusters with no impact on application availability. Replicate across globally distributed data centers to load balance workloads and prevent downtime from regional outages. Secure your data at rest and in motion, and ensure compliance with security and privacy standards. Easily integrate with your organization's authentication and authorization system. Enable full data and user activity auditing. Create automated schedules for full and incremental backups. Restore your cluster to the last stable state with snapshots and point-in-time recovery. -
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Databend
Databend
Databend is a modern, cloud-native data warehouse built to deliver high-performance, cost-efficient analytics for large-scale data processing. It is designed with an elastic architecture that scales dynamically to meet the demands of different workloads, ensuring efficient resource utilization and lower operational costs. Written in Rust, Databend offers exceptional performance through features like vectorized query execution and columnar storage, which optimize data retrieval and processing speeds. Its cloud-first design enables seamless integration with cloud platforms, and it emphasizes reliability, data consistency, and fault tolerance. Databend is an open source solution, making it a flexible and accessible choice for data teams looking to handle big data analytics in the cloud.Starting Price: Free -
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Apache Druid
Druid
Apache Druid is an open source distributed data store. Druid’s core design combines ideas from data warehouses, timeseries databases, and search systems to create a high performance real-time analytics database for a broad range of use cases. Druid merges key characteristics of each of the 3 systems into its ingestion layer, storage format, querying layer, and core architecture. Druid stores and compresses each column individually, and only needs to read the ones needed for a particular query, which supports fast scans, rankings, and groupBys. Druid creates inverted indexes for string values for fast search and filter. Out-of-the-box connectors for Apache Kafka, HDFS, AWS S3, stream processors, and more. Druid intelligently partitions data based on time and time-based queries are significantly faster than traditional databases. Scale up or down by just adding or removing servers, and Druid automatically rebalances. Fault-tolerant architecture routes around server failures. -
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Oracle Database
Oracle
Oracle database products offer customers cost-optimized and high-performance versions of Oracle Database, the world's leading converged, multi-model database management system, as well as in-memory, NoSQL, and MySQL databases. Oracle Autonomous Database, available on-premises via Oracle Cloud@Customer or in the Oracle Cloud Infrastructure, enables customers to simplify relational database environments and reduce management workloads. Oracle Autonomous Database eliminates the complexity of operating and securing Oracle Database while giving customers the highest levels of performance, scalability, and availability. Oracle Database can be deployed on-premises when customers have data residency and network latency concerns. Customers with applications that are dependent on specific Oracle database versions have complete control over the versions they run and when those versions change. -
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Hazelcast Jet
Hazelcast
Hazelcast Jet, Application performance at scale. Simplified. Our platform lets you build the fastest applications. Access a scalable, shared pool of RAM across a cluster of computers. The industry's most comprehensive in-memory computing platform The fastest in-memory data grid, combined with third-generation high-speed event processing, delivered through the cloud. Hazelcast Delivers. New data-enabled applications can deliver transformative business power – if they meet today’s requirement of immediacy. The Hazelcast platform lets you build the fastest applications by accessing a scalable, shared pool of RAM across a cluster of computers. Hazelcast’s distributed architecture provides redundancy for continuous cluster up-time and always available data to serve the most demanding applications. Capacity grows elastically with demand, without compromising performance or availability. Hazelcast In-Memory solutions are complementary to databases and orders of magnitude faster. -
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Altibase
Altibase
Altibase is an enterprise-grade, high-performance and relational open source database. A single database that delivers high-intensity data processing through an in-memory database portion and large storage capacity through an on-disk database portion. 10 times faster than conventional on-disk databases. Clients have consistently chosen Altibase over Oracle, IBM, Microsoft, and others. Altibase has replaced many traditional on-disk databases in various industries that require real time solutions since 1999. Altibase now has over 650 global enterprise clients including 8 Fortune Global 500 companies with thousands of mission-critical deployments worldwide. Product maturity rich with function and feature. Altibase is open source which includes its cutting-edge scale-out technology, sharding. No license costs with flexible and competitive subscription fees. 20 years’ accumulated know-how of dealing with over 6,000 mission-critical use cases. -
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SwayDB
SwayDB
Embeddable persistent and in-memory key-value storage engine for high performance & resource efficiency. Designed to be efficient at managing bytes on-disk and in-memory by recognising reoccurring patterns in serialised bytes without restricting the core implementation to any specific data model (SQL, NoSQL etc) or storage type (Disk or RAM). The core provides many configurations that can be manually tuned for custom use-cases, but we aim implement automatic runtime tuning when we are able to collect and analyse runtime machine statistics & read-write patterns. Manage data by creating familiar data structures like Map, Set, Queue, SetMap, MultiMap that can easily be converted to native Java and Scala collections. Perform conditional updates/data modifications with any Java, Scala or any native JVM code - No query language. -
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Graph Engine
Microsoft
Graph Engine (GE) is a distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine. The distributed RAM store provides a globally addressable high-performance key-value store over a cluster of machines. Through the RAM store, GE enables the fast random data access power over a large distributed data set. The capability of fast data exploration and distributed parallel computing makes GE a natural large graph processing platform. GE supports both low-latency online query processing and high-throughput offline analytics on billion-node large graphs. Schema does matter when we need to process data efficiently. Strongly-typed data modeling is crucial for compact data storage, fast data access, and clear data semantics. GE is good at managing billions of run-time objects of varied sizes. One byte counts as the number of objects goes large. GE provides fast memory allocation and reallocation with high memory ratios. -
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Red Hat Data Grid
Red Hat
Red Hat® Data Grid is an in-memory, distributed, NoSQL datastore solution. Your applications can access, process, and analyze data at in-memory speed to deliver a superior user experience. High performance, elastic scalability, always available. Quickly access your data through fast, low-latency data processing using memory (RAM) and distributed parallel execution. Achieve linear scalability with data partitioning and distribution across cluster nodes. Gain high availability through data replication across cluster nodes. Attain fault tolerance and recover from disaster through cross-datacenter geo-replication and clustering. Gain development flexibly and greater productivity with a highly versatile, functionally rich NoSQL data store. Obtain comprehensive data security with encryption and role-based access. Data Grid 7.3.10 provides a security enhancement to address a CVE. You must upgrade any Data Grid 7.3 deployments to version 7.3.10 as soon as possible. -
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Azure Synapse Analytics
Microsoft
Azure Synapse is Azure SQL Data Warehouse evolved. Azure Synapse is a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless or provisioned resources—at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs. -
45
StarRocks
StarRocks
Whether you're working with a single table or multiple, you'll experience at least 300% better performance on StarRocks compared to other popular solutions. From streaming data to data capture, with a rich set of connectors, you can ingest data into StarRocks in real time for the freshest insights. A query engine that adapts to your use cases. Without moving your data or rewriting SQL, StarRocks provides the flexibility to scale your analytics on demand with ease. StarRocks enables a rapid journey from data to insight. StarRocks' performance is unmatched and provides a unified OLAP solution covering the most popular data analytics scenarios. Whether you're working with a single table or multiple, you'll experience at least 300% better performance on StarRocks compared to other popular solutions. StarRocks' built-in memory-and-disk-based caching framework is specifically designed to minimize the I/O overhead of fetching data from external storage to accelerate query performance.Starting Price: Free -
46
ScyllaDB
ScyllaDB
ScyllaDB is the database for data-intensive apps that require high performance and low latency. It enables teams to harness the ever-increasing computing power of modern infrastructures – eliminating barriers to scale as data grows. Unlike any other database, ScyllaDB is a distributed NoSQL database fully compatible with Apache Cassandra and Amazon DynamoDB, yet is built with deep architectural advancements that enable exceptional end-user experiences at radically lower costs. Over 400 game-changing companies like Disney+ Hotstar, Expedia, FireEye, Discord, Zillow, Starbucks, Comcast, and Samsung use ScyllaDB for their toughest database challenges. ScyllaDB is available as free open source software, a fully-supported enterprise product, and a fully managed database-as-a-service (DBaaS) on multiple cloud providers. -
47
Tarantool
Tarantool
Corporations need a way to ensure uninterrupted operation of their systems, high speed of data processing, and reliability of storage. The in-memory technologies have proven themselves well in solving these problems. For more than 10 years, Tarantool has been helping companies all over the world build smart caches, data marts, and golden client profiles while saving server capacity. Reduce the cost of storing credentials compared to siloed solutions and improve the service and security of client applications. Reduce data management costs of maintaining a large number of disparate systems that store customer identities. Increase sales by improving the speed and quality of customer recommendations for goods or services through the analysis of user behavior and user data. Improve mobile and web channel service by accelerating frontends to reduce user outflow. IT systems of large organizations operate in a closed loop of a local network, where data circulates unprotected. -
48
Upsolver
Upsolver
Upsolver makes it incredibly simple to build a governed data lake and to manage, integrate and prepare streaming data for analysis. Define pipelines using only SQL on auto-generated schema-on-read. Easy visual IDE to accelerate building pipelines. Add Upserts and Deletes to data lake tables. Blend streaming and large-scale batch data. Automated schema evolution and reprocessing from previous state. Automatic orchestration of pipelines (no DAGs). Fully-managed execution at scale. Strong consistency guarantee over object storage. Near-zero maintenance overhead for analytics-ready data. Built-in hygiene for data lake tables including columnar formats, partitioning, compaction and vacuuming. 100,000 events per second (billions daily) at low cost. Continuous lock-free compaction to avoid “small files” problem. Parquet-based tables for fast queries. -
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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. -
50
ClickHouse
ClickHouse
ClickHouse is a fast open-source OLAP database management system. It is column-oriented and allows to generate analytical reports using SQL queries in real-time. ClickHouse's performance exceeds comparable column-oriented database management systems currently available on the market. It processes hundreds of millions to more than a billion rows and tens of gigabytes of data per single server per second. ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency. ClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure.
