Alternatives to Speedb

Compare Speedb alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Speedb in 2026. Compare features, ratings, user reviews, pricing, and more from Speedb competitors and alternatives in order to make an informed decision for your business.

  • 1
    Amazon DynamoDB
    Amazon DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale. It's a fully managed, multi-region, Multimaster, durable database with built-in security, backup and restore, and in-memory caching for internet-scale applications. DynamoDB can handle more than 10 trillion requests per day and can support peaks of more than 20 million requests per second. Many of the world's fastest-growing businesses such as Lyft, Airbnb, and Redfin as well as enterprises such as Samsung, Toyota, and Capital One depend on the scale and performance of DynamoDB to support their mission-critical workloads. Focus on driving innovation with no operational overhead. Build out your game platform with player data, session history, and leaderboards for millions of concurrent users. Use design patterns for deploying shopping carts, workflow engines, inventory tracking, and customer profiles. DynamoDB supports high-traffic, extreme-scaled events.
  • 2
    RocksDB

    RocksDB

    RocksDB

    RocksDB uses a log structured database engine, written entirely in C++, for maximum performance. Keys and values are just arbitrarily-sized byte streams. RocksDB is optimized for fast, low latency storage such as flash drives and high-speed disk drives. RocksDB exploits the full potential of high read/write rates offered by flash or RAM. RocksDB provides basic operations such as opening and closing a database, reading and writing to more advanced operations such as merging and compaction filters. RocksDB is adaptable to different workloads. From database storage engines such as MyRocks to application data caching to embedded workloads, RocksDB can be used for a variety of data needs.
  • 3
    TerarkDB

    TerarkDB

    Terark

    TerarkDB is a core product of Terark. It is a RocksDB distribution that powered by ©™Terark algorithms. with these algorithms, TerarkDB is able to store more data and access much faster than official RocksDB(3+X more data and 10+X faster) on same hardware. TerarkDB is completely compatible(binary compatible) with official RocksDB. We forked RocksDB and made a few changes to fit our algorithms, we've added it as submodule rocksdb here. Our changes for RocksDB does not change any RocksDB API, and does not have any extra dependencies, say, Terark modified RocksDB does not depend on TerarkZipTable(Without TerarkZipTable, Terark RocksDB works exactly same as official RocksDB).
  • 4
    Codehooks

    Codehooks

    Codehooks

    Codehooks is a new and simplified backend-as-a-service to create complete API backends with JavaScript / Node.JS. Enjoy smooth and fast backend development with ZERO config serverless JavaScript/TypeScript/Node.js with integrated NoSQL document Database, Key-Value store, CRON Jobs and Queue Workers. The document database is built with RocksDB and provides a MongoDB-ish query language.
  • 5
    LeanXcale

    LeanXcale

    LeanXcale

    LeanXcale is a fast and scalable database that combines the characteristics of SQL and NoSQL. It is built to ingest massive batch and real-time data pipelines and make it available through SQL or GIS for any use, such as operational applications, analytics, dashboarding, or machine learning processing. No matter what stack you use, LeanXcale provides you both SQL and NoSQL interfaces. KiVi storage engine is a relational key-value data store. Users can access the data not only through the standard SQL API but also through a direct ACID key-value interface. This key-value interface allows users to perform data ingestion at very high rates and very efficiently by avoiding SQL processing overhead. Highly-scalable, efficient and distributed storage engine distributed data along the cluster to improve the performance and increase the reliability.
    Starting Price: $0.127 per GB per month
  • 6
    LevelDB

    LevelDB

    Google

    LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values. Keys and values are arbitrary byte arrays. Data is stored sorted by key. Callers can provide a custom comparison function to override the sort order. Multiple changes can be made in one atomic batch. Users can create a transient snapshot to get a consistent view of data. Forward and backward iteration is supported over the data. Data is automatically compressed using the Snappy compression library. External activity (file system operations etc.) is relayed through a virtual interface so users can customize the operating system interactions. We use a database with a million entries. Each entry has a 16 byte key, and a 100 byte value. Values used by the benchmark compress to about half their original size. We list the performance of reading sequentially in both the forward and reverse direction, and also the performance of a random lookup.
  • 7
    InterSystems Caché
    InterSystems Caché® is a high-performance database that powers transaction processing applications around the world. It is used for everything from mapping a billion stars in the Milky Way, to processing a billion equity trades in a day, to managing smart energy grids. Caché is a multi-model (object, relational, key-value) DBMS and application server developed by InterSystems. InterSystems Caché provides several APIs to operate with same data simultaneously: key-value, relational, object, document, multi-dimensional. Data can be managed via SQL, Java, node.js, .NET, C++, Python. Caché also provides an application server which hosts web apps (CSP), REST, SOAP, web sockets and other types of TCP access for Caché data.
  • 8
    BoltDB

    BoltDB

    BoltDB

    Bolt is a pure Go key/value store inspired by Howard Chu's LMDB project. The goal of the project is to provide a simple, fast, and reliable database for projects that don't require a full database server such as Postgres or MySQL. Since Bolt is meant to be used as such a low-level piece of functionality, simplicity is key. The API will be small and only focus on getting values and setting values. That's it. The original goal of Bolt was to provide a simple pure Go key/value store and to not bloat the code with extraneous features. To that end, the project has been a success. However, this limited scope also means that the project is complete. Maintaining an open source database requires an immense amount of time and energy. Changes to the code can have unintended and sometimes catastrophic effects so even simple changes require hours and hours of careful testing and validation.
  • 9
    Oracle Berkeley DB
    Berkeley DB is a family of embedded key-value database libraries providing scalable high-performance data management services to applications. The Berkeley DB products use simple function-call APIs for data access and management. Berkeley DB enables the development of custom data management solutions, without the overhead traditionally associated with such custom projects. Berkeley DB provides a collection of well-proven building-block technologies that can be configured to address any application need from the hand-held device to the data center, from a local storage solution to a world-wide distributed one, from kilobytes to petabytes.
  • 10
    InterSystems IRIS

    InterSystems IRIS

    InterSystems

    InterSystems IRIS is a complete cloud-first data platform that includes a multi-model transactional data management engine, an application development platform, and interoperability engine, and an open analytics platform. It is the next generation of our proven data management software.It includes the capabilities of InterSystems Cache and Ensemble, plus a wealth of exciting new capabilities to make it easy to build and deploy cloud based, analytics-intensive enterprise applications with even greater performance and scalability. InterSystems IRIS provides a set of APIs to operate with transactional persistent data simultaneously: key-value, relational, object, document, multidimensional. Data can be managed by SQL, Java, node.js, .NET, C++, Python, and native server-side ObjectScript language. InterSystems IRIS includes
  • 11
    HugeGraph

    HugeGraph

    HugeGraph

    HugeGraph is a fast-speed and highly-scalable graph database. Billions of vertices and edges can be easily stored into and queried from HugeGraph due to its excellent OLTP ability. As compliance to Apache TinkerPop 3 framework, various complicated graph queries can be accomplished through Gremlin (a powerful graph traversal language). Among its features, it provides compliance to Apache TinkerPop 3, supporting Gremlin. Schema Metadata Management, including VertexLabel, EdgeLabel, PropertyKey and IndexLabel. Multi-type Indexes, supporting exact query, range query and complex conditions combination query. Plug-in Backend Store Driver Framework, supporting RocksDB, Cassandra, ScyllaDB, HBase and MySQL now and easy to add other backend store driver if needed. Integration with Hadoop/Spark. HugeGraph relies on the TinkerPop framework, we refer to the storage structure of Titan and the schema definition of DataStax.
  • 12
    SwayDB

    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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    upscaledb

    upscaledb

    upscaledb

    upscaledb is a fast key-value database which optimizes storage and algorithms for your specific data types. Optional compression further reduces file size and I/O, and can keep more data in memory to increase performance and scalability when running full-table scans to query and analyze the data. upscaledb can be used to build all functions of a typical SQL database, tailored to the specific needs of your application, and directly linked into your program. Its blazingly fast analytical functions and database cursors make it a natural fit to process data whenever a SQL database is not fast enough. Applications using upscaledb are deployed on tens of millions of desktops, but also on cloud instances, cell phones and other embedded devices. This benchmark runs a full-table scan over 50 million records and retrieves the maximum. The records are configured as uint32 values.
  • 14
    Lucid KV

    Lucid KV

    Lucid KV

    Lucid is currently in a development stage but we want to achieve a fast, secure and distributed key-value store accessible through an HTTP API, we also want to propose persistence, encryption, WebSocket streaming, replication and a lot of features. Private Keys Storing, IoT (to collect and save statistics data), Distributed cache, service discovery, distributed configuration, blob storage etc.
  • 15
    Apache Accumulo

    Apache Accumulo

    Apache Corporation

    With Apache Accumulo, users can store and manage large data sets across a cluster. Accumulo uses Apache Hadoop's HDFS to store its data and Apache ZooKeeper for consensus. While many users interact directly with Accumulo, several open source projects use Accumulo as their underlying store. To learn more about Accumulo, take the Accumulo tour, read the user manual and run the Accumulo example code. Feel free to contact us if you have any questions. Accumulo has a programming mechanism (called Iterators) that can modify key/value pairs at various points in the data management process. Every Accumulo key/value pair has its own security label which limits query results based off user authorizations. Accumulo runs on a cluster using one or more HDFS instances. Nodes can be added or removed as the amount of data stored in Accumulo changes.
  • 16
    ArcadeDB

    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
  • 17
    Infinispan

    Infinispan

    Infinispan

    Infinispan is an open-source in-memory data grid that offers flexible deployment options and robust capabilities for storing, managing, and processing data. Infinispan provides a key/value data store that can hold all types of data, from Java objects to plain text. Infinispan distributes your data across elastically scalable clusters to guarantee high availability and fault tolerance, whether you use Infinispan as a volatile cache or a persistent data store. Infinispan turbocharges applications by storing data closer to processing logic, which reduces latency and increases throughput. Available as a Java library, you simply add Infinispan to your application dependencies and then you’re ready to store data in the same memory space as the executing code.
  • 18
    BergDB

    BergDB

    BergDB

    Welcome! BergDB is a Java/.NET database designed to be simple and efficient. It was created for us developers who prefer to focus on our specific task, rather then spend time on database issues. BergDB has: simple key-value storage, ACID transactions, historic queries, efficient concurrency control, secondary indexes, fast append-only storage, replication, transparent object serialization and more. BergDB is an embedded, open-source, document-oriented, schemaless, NoSQL database. BergDB is built from the ground up to execute transactions exceptionally fast. And there are no compromises, all writes to the database are made in ACID transactions with the highest possible level of consistency (in SQL-speak: serializable isolation level). Historic queries are important when previous data states are of interest, and also as a fast way to handle concurrency. A read operation never locks anything in BergDB.
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    etcd

    etcd

    etcd

    etcd is a strongly consistent, distributed key-value store that provides a reliable way to store data that needs to be accessed by a distributed system or cluster of machines. It gracefully handles leader elections during network partitions and can tolerate machine failure, even in the leader node. Store data in hierarchically organized directories, as in a standard filesystem. Watch specific keys or directories for changes and react to changes in values.
  • 20
    OrbitDB

    OrbitDB

    OrbitDB

    ​OrbitDB is a serverless, distributed, peer-to-peer database that utilizes IPFS for data storage and Libp2p Pubsub for automatic synchronization across peers. It employs Merkle-CRDTs to ensure conflict-free database writes and merges, making it suitable for decentralized applications, blockchain integrations, and local-first web apps. OrbitDB offers various database types tailored to different use cases: 'events' for immutable append-only logs, 'documents' for JSON document storage indexed by a specified key, 'keyvalue' for traditional key-value pairs, and 'keyvalue-indexed' for LevelDB-indexed key-value data. All these databases are built atop OpLog, an immutable, cryptographically verifiable, operation-based CRDT structure. The JavaScript implementation supports both browser and Node.js environments, with a Go version maintained by the Berty project.
    Starting Price: Free
  • 21
    VMware Tanzu GemFire
    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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    Pravega

    Pravega

    Pravega

    Distributed messaging systems such as Kafka and Pulsar have provided modern Pub/Sub infrastructure well suited for today’s data-intensive applications. Pravega further enhances this popular programming model and provides a cloud-native streaming infrastructure, enabling a wider swath of applications. Pravega streams are durable, consistent, and elastic, while natively supporting long-term data retention. Pravega solves architecture-level problems that former topic-based systems Kafka and Pulsar have failed to solve, such as auto-scaling of partitions or maintaining high performance for a large number of partitions. It enhances the range of supported applications by efficiently handling both small events as in IoT and larger data as in videos for computer vision/video analytics. By providing abstractions beyond streams, Pravega also enables replicating application state and storing key-value pairs.
  • 23
    FoundationDB

    FoundationDB

    FoundationDB

    FoundationDB is multi-model, meaning you can store many types data in a single database. All data is safely stored, distributed, and replicated in the Key-Value Store component. FoundationDB is easy to install, grow, and manage. It has a distributed architecture that gracefully scales out, and handles faults while acting like a single ACID database. FoundationDB provides amazing performance on commodity hardware, allowing you to support very heavy loads at low cost. FoundationDB has been running in production for years and been hardened with lessons learned. Backing FoundationDB up is an unmatched testing system based on a deterministic simulation engine. We encourage your participation in our open-source community! Join us in technical and user discussions on the community forums, and learn how to contribute.
  • 24
    Riak KV
    At Riak, we are distributed systems experts and we work with Application teams to overcome these distributed system challenges. Riak’s Riak® is a distributed NoSQL database that delivers unmatched Resiliency beyond typical “high availability” offerings. Innovative technology to ensure data accuracy and never lose a write. Massive scale on commodity hardware. Common code foundation with true multi-model support. Riak® provides all this, while still focused on ease of operations. Chose Riak® KV flexible key-value data model for web scale profile and session management, real-time big data, catalog, content management, customer 360, digital messaging, and more use cases. Chose Riak® TS for IoT and time series use cases. When seconds of latency can cost thousands of dollars and an outage millions, the call for scalable, highly available databases that are easy to operationalize is resoundingly clear. Riak performs as promised and keeps the lights on.
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    Valkey

    Valkey

    Valkey

    ​Valkey is an open source high-performance key/value datastore that supports a variety of workloads, such as caching, message queues, and can act as a primary database. It is backed by the Linux Foundation, ensuring it will remain open source forever. Valkey can run as either a standalone daemon or in a cluster, with options for replication and high availability. It natively supports a rich collection of datatypes, including strings, numbers, hashes, lists, sets, sorted sets, bitmaps, hyperloglogs, and more. You can operate on data structures in-place with an expressive collection of commands. Valkey also supports native extensibility with built-in scripting support for Lua and supports module plugins to create new commands, data types, and more. Valkey 8.1 introduces several performance improvements that reduce latency, increase throughput, and lower memory usage.
    Starting Price: Free
  • 26
    Kyoto Tycoon

    Kyoto Tycoon

    Altice Labs

    Kyoto Tycoon is a lightweight network server on top of the Kyoto Cabinet key-value database, built for high-performance and concurrency. Some of its features include. It has its own fully-featured protocol based on HTTP and a (limited) binary protocol for even better performance. There are several client libraries implementing them for multiple languages (we're maintaining one for Python here). It can also be configured with simultaneous support for the memcached protocol, with some limitations on available data update commands. This is useful if you wish to replace memcached in larger-than-memory/persistency scenarios. Here you can find improved versions of the latest available upstream releases, intended to be used together and tested in real-world production environments. The changes include bug fixes, minor new features and packaging for a few Linux distributions.
  • 27
    E-MapReduce
    EMR is an all-in-one enterprise-ready big data platform that provides cluster, job, and data management services based on open-source ecosystems, such as Hadoop, Spark, Kafka, Flink, and Storm. Alibaba Cloud Elastic MapReduce (EMR) is a big data processing solution that runs on the Alibaba Cloud platform. EMR is built on Alibaba Cloud ECS instances and is based on open-source Apache Hadoop and Apache Spark. EMR allows you to use the Hadoop and Spark ecosystem components, such as Apache Hive, Apache Kafka, Flink, Druid, and TensorFlow, to analyze and process data. You can use EMR to process data stored on different Alibaba Cloud data storage service, such as Object Storage Service (OSS), Log Service (SLS), and Relational Database Service (RDS). You can quickly create clusters without the need to configure hardware and software. All maintenance operations are completed on its Web interface.
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    LMCache

    LMCache

    LMCache

    LMCache is an open source Knowledge Delivery Network (KDN) designed as a caching layer for large language model serving that accelerates inference by reusing KV (key-value) caches across repeated or overlapping computations. It enables fast prompt caching, allowing LLMs to “prefill” recurring text only once and then reuse those stored KV caches, even in non-prefix positions, across multiple serving instances. This approach reduces time to first token, saves GPU cycles, and increases throughput in scenarios such as multi-round question answering or retrieval augmented generation. LMCache supports KV cache offloading (moving cache from GPU to CPU or disk), cache sharing across instances, and disaggregated prefill, which separates the prefill and decoding phases for resource efficiency. It is compatible with inference engines like vLLM and TGI and supports compressed storage, blending techniques to merge caches, and multiple backend storage options.
    Starting Price: Free
  • 29
    KVdb

    KVdb

    Pilvy

    Stop wasting time setting up NoSQL databases. Get a key-value database and web API up and running in seconds. Perfect for serverless apps, prototyping, metrics, and more. Simplest API on the planet. Whether you use one bucket or a thousand buckets to store your keys, KVdb makes it easy to read and write key-value data for any business use case. Secure your database by using access tokens that restrict which keys users can read and write. Great for most apps with user accounts. Use curl or your favorite HTTP client library. Create a bucket, optionally protected against key enumeration and deletion. Values can be up to 16 KB in size. Easily increment or decrement number values. Store keys without expiration with our Pro plan, write custom bucket scripts, and use access tokens for controlling access to buckets.
    Starting Price: $10 per month
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    PLAXIS 2D

    PLAXIS 2D

    Bentley Systems

    Every project is challenging, but the geotechnical analysis doesn’t have to be. PLAXIS 2D provides the power of fast computations. Perform advanced finite element or limit equilibrium analysis of soil and rock deformation and stability, as well as soil structure interaction, groundwater, and heat flow. PLAXIS 2D is a powerful and user-friendly finite-element (FE) software for 2D analysis of deformation and stability in geotechnical engineering and rock mechanics. PLAXIS is used worldwide by top engineering companies and institutions in the civil and geotechnical engineering industry. PLAXIS 2D is ideal for a range of applications from excavations, embankments, and foundations to tunneling, mining, oil and gas, and reservoir geomechanics. PLAXIS 2D includes all the essentials to perform deformation and safety analysis for soil and rock that do not require the consideration of creep, steady state groundwater or thermal flow, consolidation analysis, or any time-dependent effects.
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    Oracle NoSQL Database
    Oracle NoSQL Database is designed to handle high-volume, high-velocity data applications requiring low-latency responses and flexible data models. It supports JSON, table, and key-value data types, and operates both on-premise and as a cloud service. The database scales elastically to meet dynamic workloads and provides distributed data storage across multiple shards, ensuring high availability and rapid failover. It includes Python, Node.js, Java, C, C#, and REST API drivers for easy application development. Additionally, it integrates with Oracle products such as IoT, Golden Gate, and Fusion Middleware. Oracle NoSQL Database Cloud Service is a fully managed service, freeing developers from backend infrastructure management. Oracle NoSQL Database Cloud Service is a fully managed database service for developers who want to focus on application development without dealing with the hassle of managing the back-end hardware and software infrastructure.
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    StarRocks

    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
  • 33
    AsparaDB

    AsparaDB

    Alibaba

    ApsaraDB for Redis is an automated and scalable tool for developers to manage data storage shared across multiple processes, applications or servers. As a Redis protocol compatible tool, ApsaraDB for Redis offers exceptional read-write capabilities and ensures data persistence by using memory and hard disk storage. ApsaraDB for Redis provides data read-write capabilities at high speed by retrieving data from in-memory caches and ensures data persistence by using both memory and hard disk storage mode. ApsaraDB for Redis supports advanced data structures such as leaderboard, counting, session, and tracking, which are not readily achievable through ordinary databases. ApsaraDB for Redis also has an enhanced edition called "Tair" . Tair has officially handled the data caching scenarios of Alibaba Group since 2009 and has proven its outstanding performance in scenarios such as Double 11 Shopping Festival.
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    MultiChain

    MultiChain

    Coin Sciences

    MultiChain helps organizations to build and deploy blockchain applications with speed. Just two simple steps to create a new blockchain, and three to connect to an existing one. Deploy unlimited blockchains per server for cross-chain applications. Issue millions of assets and tokens, all tracked and verified at the network level. Perform safe multi-asset and multi-party atomic exchange transactions. Create multiple key-value, time series or identity databases. Store data on- or off-chain. Ideal for data sharing, timestamping and encrypted archiving. Optionally control who can connect, send and receive transactions, create assets, streams and blocks. Each blockchain is as open or as closed as you need.
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    Tensormesh

    Tensormesh

    Tensormesh

    Tensormesh is a caching layer built specifically for large-language-model inference workloads that enables organizations to reuse intermediate computations, drastically reduce GPU usage, and accelerate time-to-first-token and latency. It works by capturing and reusing key-value cache states that are normally thrown away after each inference, thereby cutting redundant compute and delivering “up to 10x faster inference” while substantially lowering GPU load. It supports deployments in public cloud or on-premises, with full observability and enterprise-grade control, SDKs/APIs, and dashboards for integration into existing inference pipelines, and compatibility with inference engines such as vLLM out of the box. Tensormesh emphasizes performance at scale, including sub-millisecond repeated queries, while optimizing every layer of inference from caching through computation.
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    Seagate CORTX
    The community-driven design delivers faster access to innovations while open source code can be tailored to your use case. Get lightning-fast access to data with exabyte-scale software that improves storage media scalability and efficiency. Optimized for HDD capacity growth, data durability, and recovery. Get the tested and supported version of CORTX bundled with our converged infrastructure solution, Lyve Drive™ Rack. We’re revolutionizing enterprise storage with Lyve Drive Rack, a tightly integrated, converged infrastructure solution that bundles up to 1.7PB with CORTX object storage, giving you the storage capacity you need, without the expensive storage software license fees. No global locks for scalable performance in the consistent object, key-value, file, and clusters. Scalable data experience, add structure to unstructured data, and enable easy, fast access, search, and analysis.
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    Azure AI Document Intelligence
    AI Document Intelligence is an AI service that applies advanced machine learning to extract text, key-value pairs, tables, and structures from documents automatically and accurately. Turn documents into usable data and shift your focus to acting on information rather than compiling it. Start with prebuilt models or create custom models tailored to your documents both on-premises and in the cloud with the AI Document Intelligence studio or SDK. Learn how to accelerate your business processes by automating text extraction with AI Document Intelligence. This webinar features hands-on demos for key use cases such as document processing, knowledge mining, and industry-specific AI model customization. Accurately extract text, key-value pairs, and tables from documents, forms, receipts, invoices, and cards of various types without manual labeling by document type, intensive coding, or maintenance. Use AI Document Intelligence custom forms, prebuilt, and layout APIs to extract information.
    Starting Price: $1.50 per 1,000 pages
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    Yandex Managed Service for Redis
    You can deploy a ready-to-use cluster in just a few minutes. DB settings are initially optimized for the cluster size you selected. If the load on your cluster increases, you can add new servers or increase their capacity in a matter of minutes. Redis stores data in key-value format, supported values include strings, arrays, dictionaries, sets, bitmasks, and other types. Redis runs in RAM and is therefore suitable for tasks that require a quick response or involve performing a large number of operations on a relatively small amount of data. Backups of database contents are GPG-encrypted. Data is secured in accordance with the requirements of local regulatory, GDPR, and ISO industry standards. Set a time limit for Yandex Managed Service for Redis to automatically delete data and optimize your data storage costs.
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    Graph Engine

    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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    AlgoDocs

    AlgoDocs

    AlgoDocs

    AlgoDocs is a powerful web-based AI Platform for Data Extraction developed using the latest technologies. Extract handwriting, tables, Key-Value Pairs, marks, and Signature detection from PDFs and image files. Export extracted data to CSV, XML, Excel, or many other integrations, such as accounting software. AlgoDocs offers a forever free subscription, with 50 pages processed every month.
    Starting Price: $23/month
  • 41
    Litestar

    Litestar

    Litestar

    Everything that's needed to build modern APIs, from data serialization and validation to websockets, ORM integration, session management, authentication and more. Litestar puts great emphasis on developer experience and performance: It's one of the fastest ASGI frameworks and developing with it is just as fast. Asynchronous at heart, but with synchronous execution not as a second class citizen: Synchronous applications run without performance penalties. Interfaces for various key/value stores that seamlessly integrate with your application and third party extensions. Response caching with minimal configuration and overhead to speed up response times. Response caching with minimal configuration and overhead to speed up response times. Session and JWT based authentication and utilities at your disposal to start building your authentication layer with ease.
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    Alibaba Cloud Tablestore
    Tablestore enables seamless expansion of data size and access concurrency through data sharding and server load balancer technologies, providing storage of and real-time access to massive structured data. Three copies of data with high consistency, full host, service high availability and data high reliability. Provides full/incremental data tunnels, seamlessly interconnecting with various products for big data analysis and real-time stream computing. Distributed architecture, single table auto scaling, support of 10-PB-level data and 10-million-level access concurrency. Multi-dimensional and multi-level security protection and resource access management to ensure data security. The low latency, high concurrency, elastic resources and Pay-As-You-Go billing method of this service enables your risk control system to always operate in optimal conditions, allowing you to strictly control transaction risks.
    Starting Price: $0.00010 per GB
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    Backbone.js

    Backbone.js

    Backbone.js

    Backbone.js gives structure to web applications by providing models with key-value binding and custom events, collections with a rich API of enumerable functions, views with declarative event handling, and connects it all to your existing API over a RESTful JSON interface. When working on a web application that involves a lot of JavaScript, one of the first things you learn is to stop tying your data to the DOM. It's all too easy to create JavaScript applications that end up as tangled piles of jQuery selectors and callbacks, all trying frantically to keep data in sync between the HTML UI, your JavaScript logic, and the database on your server. For rich client-side applications, a more structured approach is often helpful. With Backbone, you represent your data as Models, which can be created, validated, destroyed, and saved to the server.
    Starting Price: Free
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    Apache Iceberg

    Apache Iceberg

    Apache Software Foundation

    Iceberg is a high-performance format for huge analytic tables. Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for engines like Spark, Trino, Flink, Presto, Hive and Impala to safely work with the same tables, at the same time. Iceberg supports flexible SQL commands to merge new data, update existing rows, and perform targeted deletes. Iceberg can eagerly rewrite data files for read performance, or it can use delete deltas for faster updates. Iceberg handles the tedious and error-prone task of producing partition values for rows in a table and skips unnecessary partitions and files automatically. No extra filters are needed for fast queries, and the table layout can be updated as data or queries change.
    Starting Price: Free
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    EdgeWorkers
    Akamai's EdgeWorkers is a serverless computing platform that enables developers to deploy custom JavaScript code at the edge, optimizing user experiences by executing logic closer to end users. This approach reduces latency by eliminating high-latency calls to origin servers, enhancing performance, and improving security by moving exposed client-side logic to the edge. EdgeWorkers supports various use cases, including AB testing, geolocation-based content delivery, data protection, privacy compliance, dynamic website personalization, traffic management, and device-based personalization. Developers can write JavaScript code and deploy it via API, CLI, or GUI, leveraging Akamai's scalable architecture that automatically manages infrastructure during growth or traffic spikes. The platform integrates with Akamai's EdgeKV, a distributed key-value store, enabling data-driven applications with low-latency data access.
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    Hazelcast

    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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    Google Cloud Bigtable
    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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    Google Cloud Memorystore
    Reduce latency with scalable, secure, and highly available in-memory service for Redis and Memcached. Memorystore automates complex tasks for open source Redis and Memcached like enabling high availability, failover, patching, and monitoring so you can spend more time coding. Start with the lowest tier and smallest size and then grow your instance with minimal impact. Memorystore for Memcached can support clusters as large as 5 TB supporting millions of QPS at very low latency. Memorystore for Redis instances are replicated across two zones and provide a 99.9% availability SLA. Instances are monitored constantly and with automatic failover—applications experience minimal disruption. Choose from the two most popular open source caching engines to build your applications. Memorystore supports both Redis and Memcached and is fully protocol compatible. Choose the right engine that fits your cost and availability requirements.
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    GridDB

    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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    HerdDB

    HerdDB

    Diennea

    HerdDB is a SQL distributed database implemented in Java. It has been designed to be embeddable in any Java Virtual Machine. It is optimized for fast "writes" and primary key read/update access patterns. HerdDB is designed to manage hundreds of tables. It is simple to add and remove hosts and to reconfigure tablespaces to easly distribute the load on multiple systems. HerdDB leverages Apache Zookeeper and Apache Bookkeeper to build a fully replicated, shared-nothing architecture without any single point of failure. At the low level HerdDB is very similar to a key-value NoSQL database. On top of that an SQL abstraction layer and JDBC Driver support enables every user to leverage existing known-how and port existing applications to HerdDB. At Diennea we developed EmailSuccess, a powerfull MTA (Mail Transfer Agent), designed to deliver millions of email messages per hour to inboxes all around the world,