eXtremeDB Alternatives

Raima Database Manager 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.

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.

Manage complex models using ArcadeDB without any compromise. Forget about Polyglot Persistence. no need for multiple databases. You can store graphs, documents, key values and time series all in one ArcadeDB Multi-Model database. Since each model is native to the database engine, you don't have to worry about translations slowing you down. ArcadeDB's engine was built with Alien Technology. It's able to crunch millions of records per second. With ArcadeDB, the traversing speed is not affected by the database size. It is always constant, whether your database has a few records or billions. ArcadeDB can work as an embedded database, on a single server and can scale up using multiple servers with Kubernetes. Flexible enough to run on any platform with a small footprint. Your data is secure. Our unbreakable fully transactional engine assures durability for mission-critical production databases. ArcadeDB uses a Raft Consensus Algorithm to maintain consistency across multiple servers.

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.

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.

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.

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.

IBM Informix® is a fast and flexible database with the ability to seamlessly integrate SQL, NoSQL/JSON, and time series and spatial data. Its versatility and ease of use make Informix a preferred solution for a wide range of environments, from enterprise data warehouses to individual application development. Also, with its small footprint and self-managing capabilities, Informix is well suited for embedded data-management solutions. IoT data demands robust processing and integration capabilities. Informix offers a hybrid database system with minimal administrative requirements and memory footprint combined with powerful functionality. Key features make Informix ideal for multi-tiered architectures that require processing at the device level, at gateway layers and in the cloud. Native encryption to protect data at rest and in motion. Support for flexible schema, multiple APIs and configurations.

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

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

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.

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.

JaguarDB enables fast ingestion of time series data, coupling location-based data. It also can index in both dimensions, space and time. Back-filling time series data is also fast (inserting large volumes of data in past time). Normally time series is a series of data points indexed in time order. In JaguarDB, the time series has a different meaning: it is both a sequence of data points and a series of tick tables holding aggregated data values at specified time spans. For example, a time series table in JaguarDB can have a base table storing data points in time order, and tick tables such as 5 minute, 15 minute, hourly, daily, weekly, monthly tables to store aggregated data within these time spans. The format for the RETENTION is the same as the TICK format, except that it can have any number of retention periods. The RETENTION specifies how long the data points in the base table should be kept.

The Open, Multi-Cloud Stack for Modern Data Apps. Built on open-source Apache Cassandra™. Global-scale and 100% uptime without vendor lock-in. Deploy on multi-cloud, on-prem, open-source, and Kubernetes. Elastic and pay-as-you-go for improved TCO. Start building faster with Stargate APIs for NoSQL, real-time, reactive, JSON, REST, and GraphQL. Skip the complexity of multiple OSS projects and APIs that don’t scale. Ideal for commerce, mobile, AI/ML, IoT, microservices, social, gaming, and richly interactive applications that must scale-up and scale-down with demand. Get building modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Use REST, GraphQL, JSON with your favorite full-stack framework Richly interactive apps that are elastic and viral-ready from Day 1. Pay-as-you-go Apache Cassandra DBaaS that scales effortlessly and affordably.

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.

InfinityDB Embedded is a Java NoSQL database, a hierarchical sorted key value store. It is high-performance, multi-core, flexible, and maintenance-free. InfinityDB Encrypted database and InfinityDB Client/Server database are now available as well. InfinityDB has the highest available performance, according to our customers and the provided performance tests: Multi-core overlapping operations scale almost linearly in thread count, threads use fair scheduling, with very low inter-thread interference, random I/O scales logarithmically in file size, with no size limit, caches grow only as used, and are packed efficiently, database open is immediate, even for recovery after abrupt exit.

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.

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.

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.

Instaclustr is the Open Source-as-a-Service company, delivering reliability at scale. We operate an automated, proven, and trusted managed environment, providing database, analytics, search, and messaging. We enable companies to focus internal development and operational resources on building cutting edge customer-facing applications. Instaclustr works with cloud providers including AWS, Heroku, Azure, IBM Cloud, and Google Cloud Platform. The company has SOC 2 certification and provides 24/7 customer support.

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.

Fauna is a data API for modern applications that facilitates rich clients with serverless backends by providing a web-native interface with support for GraphQL and custom business logic, frictionless integration with the serverless ecosystem, a no compromise multi-cloud architecture you can trust and grow with and total freedom from database operations. Instantly create multiple databases in one account leveraging multi-tenancy for development or customer-facing use case. Create a distributed database across one geography or the globe in just three clicks and easily import existing data. Scale seamlessly without ever managing servers, clusters, data partitioning, or replication. Track usage and consumption-based billing in near real time via a dashboard.

Machbase, a time-series database that stores and analyzes a lot of sensor data from various facilities in real time, is the only DBMS solution that can process and analyze big data at high speed. Experience the amazing speed of Machbase! It is the most innovative product that enables real-time processing, storage, and analysis of sensor data. High speed sensor data storage and inquiry for sensor data by embedding DBMS in an Edge devices. Best data storage and extraction performance by DBMS running in a single server. Configuring Multi-node cluster with the advantages of availability and scalability. Total management solution of Edge computing for device, connectivity and data.

Smart DIH is an operational data hub that powers real-time modern applications. It unleashes the power of customers’ data by transforming data silos into assets, turning organizations into data-driven enterprises. Smart DIH consolidates data from multiple heterogeneous systems into a highly performant data layer. Low code tools empower data professionals to deliver data microservices in hours, shortening developing cycles and ensuring data consistency across all digital channels. XAP Skyline is a cloud-native, in memory data grid (IMDG) and developer framework designed for mission critical, cloud-native apps. XAP Skyline delivers maximal throughput, microsecond latency and scale, while maintaining transactional consistency. It provides extreme performance, significantly reducing data access time, which is crucial for real-time decisioning, and transactional applications. XAP Skyline is used in financial services, retail, and other industries where speed and scalability are critical.

Telegraf is the open source server agent to help you collect metrics from your stacks, sensors and systems. Telegraf is a plugin-driven server agent for collecting and sending metrics and events from databases, systems, and IoT sensors. Telegraf is written in Go and compiles into a single binary with no external dependencies, and requires a very minimal memory footprint. Telegraf can collect metrics from a wide array of inputs and write them into a wide array of outputs. It is plugin-driven for both collection and output of data so it is easily extendable. It is written in Go, which means that it is a compiled and standalone binary that can be executed on any system with no need for external dependencies, no npm, pip, gem, or other package management tools required. With 300+ plugins already written by subject matter experts on the data in the community, it is easy to start collecting metrics from your end-points.

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.

Real-Time Analytics on Raw Data. Live ingest from S3, Kafka, DynamoDB & more. Explore raw data as SQL tables. Build amazing data-driven applications & live dashboards in minutes. Rockset is a serverless search and analytics engine that powers real-time apps and live dashboards. Operate directly on raw data, including JSON, XML, CSV, Parquet, XLSX or PDF. Plug data from real-time streams, data lakes, databases, and data warehouses into Rockset. Ingest real-time data without building pipelines. Rockset continuously syncs new data as it lands in your data sources without the need for a fixed schema. Use familiar SQL, including joins, filters, and aggregations. It’s blazing fast, as Rockset automatically indexes all fields in your data. Serve fast queries that power the apps, microservices, live dashboards, and data science notebooks you build. Scale without worrying about servers, shards, or pagers.

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.

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.

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.

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.

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.

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.

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.

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.

ADISRA SmartView™ 4.0 HMI/SCADA Visualization Software ADISRA SmartView is a powerful, Windows and Linux-based, desktop software tool that builds robust HMI, SCADA, and Client-Server programs for industrial automation applications. ADISRA SmartView provides the integrated features and functionality necessary to quickly create projects and connect to industry-standard modules, components and devices. With ADISRA SmartView, you have the power to create powerful HMI and SCADA applications and easily edit them at any time. ADISRA SmartView is loaded with communication drivers to easily integrate different modules, components and devices. You can store and acquire data from external sources (OPCs, Databases, PI-OsiSoft, IoT and Edge Devices, PLCs, and the Cloud). Integrated Window-Linux based development environment with all easily-recognized features to build HMI, SCADA, OEE and IIoT applications.

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.

IBM Cloud Databases are open source data stores for enterprise application development. Built on a Kubernetes foundation, they offer a database platform for serverless applications. They are designed to scale storage and compute resources seamlessly without being constrained by the limits of a single server. Natively integrated and available in the IBM Cloud console, these databases are now available through a consistent consumption, pricing, and interaction model. They aim to provide a cohesive experience for developers that include access control, backup orchestration, encryption key management, auditing, monitoring, and logging.

Voldemort is not a relational database, it does not attempt to satisfy arbitrary relations while satisfying ACID properties. Nor is it an object database that attempts to transparently map object reference graphs. Nor does it introduce a new abstraction such as document-orientation. It is basically just a big, distributed, persistent, fault-tolerant hash table. For applications that can use an O/R mapper like active-record or hibernate this will provide horizontal scalability and much higher availability but at great loss of convenience. For large applications under internet-type scalability pressure, a system may likely consist of a number of functionally partitioned services or APIs, which may manage storage resources across multiple data centers using storage systems which may themselves be horizontally partitioned. For applications in this space, arbitrary in-database joins are already impossible since all the data is not available in any single database.

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.

In-memory computing with TIBCO ActiveSpaces® in-memory data grid provides a distributed, consistent, fault-tolerant database that supports scalability for mixed read/write workloads and full system of record capabilities. ActiveSpaces® technology draws on available server memory but also stores it to local disks for data safety and for scaling to handle the processing of the largest data volumes. With the ActiveSpaces solution, contextual, reference, and operational data normally housed in back-end applications can be stored in memory for lightning-fast performance. It's the kind of performance you need to delight customers and beat the other guys. Any data stored anywhere can now be included in real-time processing and decision-making. ActiveSpaces technology handles large data volumes. You can dynamically add capacity without a system restart. Persistence is distributed, so it's often possible to remove costly databases and associated failure points from legacy implementations.

Rapid SCADA is an open-source industrial automation platform. The out-of-the-box software provides tools for rapid creation of monitoring and control systems. In case of large implementation, Rapid SCADA is used as a core for the development of custom SCADA and MES solutions for a Customer. Open source is the key to software transparency and security. The licensing model permits the creation of new derivative software products. Rapid SCADA is a perfect choice for creating large distributed industrial automation systems. Rapid SCADA runs on servers, embedded computers and in the cloud. Rapid SCADA nodes exchange information between themselves and interact with external databases in real-time. Acquisitions and dispositions are automatically created in your electronic bound book when you receive and sell through our 100% ATF Compliant POS system.

Use Apache HBase™ when you need random, realtime read/write access to your Big Data. This project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. Automatic failover support between RegionServers. Easy to use Java API for client access. Thrift gateway and a REST-ful Web service that supports XML, Protobuf, and binary data encoding options. Support for exporting metrics via the Hadoop metrics subsystem to files or Ganglia; or via JMX.

BangDB natively integrates AI, streaming, graph, analytics within the DB itself to enable users to deal with complex data of different kinds, such as text, images, videos, objects etc. for real time data processing and analysis Ingest or stream any data, process it, train models, do prediction, find patterns, take action and automate all these to enable use cases such as IOT monitoring, fraud or disruption prevention, log analysis, lead generation, 1-on-1 personalisation and many more. Today’s use cases require different kinds of data to be ingested, processed, and queried at the same time for a given problem. BangDB supports most of the useful data formats to allow user to solve the problem in a simple manner. Rise of real time data pushes for real time streaming and predictive data analytics for advanced and optimized business operations.

Tatsoft’s FactoryStudio gives you the tools to rapidly design powerful and secure industrial applications! Features: real-time data modeling, data logging, MQTT broker/client/spB, audit trail, alarms & events, visual SQL query database gateway, high-performance smart displays, HTML5 dashboards, WPF drawing tools, iOS app, trends & annotations, reporting & more! You can program scripts in C#, VB.NET, JavaScript and Python. With ZERO install on the client side, and only 2 minutes install server side, you can be up and building performance improving applications in no time! Includes dozens of built-in native protocol drivers to PLCs, DCSs, and support for other industry standards, like OPC and MQTT. Need a driver we don’t have yet? We also have a toolkit for protocol driver development! FactoryStudio can act as your data hub for everything in your industrial ecosystem: your link between IT and OT, your real-time devices, and your SQL data sources with easy data-binding

With an in-memory, columnar database and MPP architecture, you can query billions of rows in seconds. Queries are distributed across all nodes in a cluster, providing linear scalability for more users and advanced analytics. MPP, in-memory, and columnar storage add up to the fastest database built for data analytics. With SaaS, cloud, on premises and hybrid deployment options you can analyze data wherever it lives. Automatic query tuning reduces maintenance and overhead. Seamless integrations and performance efficiency gets you more power at a fraction of normal infrastructure costs. Smart, in-memory query processing allowed this social networking company to boost performance, processing 10B data sets a year. A single data repository and speed engine to accelerate critical analytics, delivering improved patient outcome and bottom line.

High-performance vectorized columnar analytics database. Consistent performance leader on TPC-H decision support benchmark over last 5 years. Industry-standard ANSI SQL:2003 support plus integration for extensive set of data formats. Updates, security, management, replication. Actian Vector is the industry’s fastest analytic database. Vector’s ability to handle continuous updates without a performance penalty makes it an Operational Data Warehouse (ODW) capable of incorporating the latest business information into your analytic decision-making. Vector achieves extreme performance with full ACID compliance on commodity hardware with the flexibility to deploy on premises, on AWS or Azure, with little or no database tuning. Actian Vector is available on Microsoft Windows for single server deployment. The distribution includes Actian Director for easy GUI based management in addition to the command line interface to easy scripting.

QuestDB is a relational column-oriented database designed for time series and event data. It uses SQL with extensions for time series to assist with real-time analytics. These pages cover core concepts of QuestDB, including setup steps, usage guides, and reference documentation for syntax, APIs and configuration. This section describes the architecture of QuestDB, how it stores and queries data, and introduces features and capabilities unique to the system. Designated timestamp is a core feature that enables time-oriented language capabilities and partitioning. Symbol type makes storing and retrieving repetitive strings efficient. Storage model describes how QuestDB stores records and partitions within tables. Indexes can be used for faster read access on specific columns. Partitions can be used for significant performance benefits on calculations and queries. SQL extensions allow performant time series analysis with a concise syntax.

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.

Quasar's brain is QuasarDB, a high-performance, distributed, column-oriented timeseries database management system designed from the ground up to deliver real-time on petascale use cases. Up to 20X less disk usage. Quasardb ingestion and compression capabilities are unmatched. Up to 10,000X faster feature extraction. QuasarDB can extract features in real-time from the raw data, thanks to the combination of a built-in map/reduce query engine, an aggregation engine that leverages SIMD from modern CPUs, and stochastic indexes that use virtually no disk space. The most cost-effective timeseries solution, thanks to its ultra-efficient resource usage, the capability to leverage object storage (S3), unique compression technology, and fair pricing model. Quasar runs everywhere, from 32-bit ARM devices to high-end Intel servers, from Edge Computing to the cloud or on-premises.