Alibaba Cloud TSDB Alternatives

StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. • Gain critical real-time insights to run your business • Seamlessly integrate data streaming and batch data • High performance in throughput and low-latency at petabyte scale • Fully-managed cloud service • Tiered storage to optimize cloud performance & spend • Fully-secure & enterprise-ready

ScaleGrid is a fully managed Database-as-a-Service (DBaaS) platform that helps you automate your time-consuming database administration tasks both in the cloud and on-premises. Easily provision, monitor, backup and scale your open source databases with high availability, advanced security, full superuser and SSH access, query analysis, and troubleshooting support to improve the performance of your deployments. Supported databases include: - MySQL - PostgreSQL - Redis™ - MongoDB® database - Greenplum™ (coming soon) The ScaleGrid platform supports both public and private clouds, including AWS, Azure, Google Cloud Platform (GCP), DigitalOcean, Linode, Oracle Cloud Infrastructure (OCI), VMware and OpenStack. Used by thousands of developers, startups, and enterprise customers including Atlassian, Meteor, and Accenture, ScaleGrid handles all your database operations at any scale so you can focus on your application performance.

Amazon Relational Database Service (Amazon RDS) makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups. It frees you to focus on your applications so you can give them the fast performance, high availability, security and compatibility they need. Amazon RDS is available on several database instance types - optimized for memory, performance or I/O - and provides you with six familiar database engines to choose from, including Amazon Aurora, PostgreSQL, MySQL, MariaDB, Oracle Database, and SQL Server. You can use the AWS Database Migration Service to easily migrate or replicate your existing databases to Amazon RDS.

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.

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.

InfluxDB is a purpose-built data platform designed to handle all time series data, from users, sensors, applications and infrastructure — seamlessly collecting, storing, visualizing, and turning insight into action. With a library of more than 250 open source Telegraf plugins, importing and monitoring data from any system is easy. InfluxDB empowers developers to build transformative IoT, monitoring and analytics services and applications. InfluxDB’s flexible architecture fits any implementation — whether in the cloud, at the edge or on-premises — and its versatility, accessibility and supporting tools (client libraries, APIs, etc.) make it easy for developers at any level to quickly build applications and services with time series data. Optimized for developer efficiency and productivity, the InfluxDB platform gives builders time to focus on the features and functionalities that give their internal projects value and their applications a competitive edge.

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.

VictoriaMetrics is a fast and scalable open source time series database and monitoring solution. It's designed to be user-friendly, allowing users to build a monitoring platform without scalability issues and with minimal operational burden. VictoriaMetrics is ideal for solving use cases with large amounts of time series data for IT infrastructure, APM, Kubernetes, IoT sensors, automotive vehicles, industrial telemetry, financial data, and other enterprise-level workloads. VictoriaMetrics is powered by several components, making it the perfect solution for collecting metrics (both push and pull models), running queries, and generating alerts. With VictoriaMetrics, you can store millions of data points per second on a single instance or scale to a high-load monitoring system across multiple data centers. Plus, it's designed to store 10x more data using the same compute and storage resources as existing solutions, making it a highly efficient choice.

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.

OpenTSDB consists of a Time Series Daemon (TSD) as well as set of command line utilities. Interaction with OpenTSDB is primarily achieved by running one or more of the independent TSDs. There is no master, no shared state so you can run as many TSDs as required to handle any load you throw at it. Each TSD uses the open source database HBase or hosted Google Bigtable service to store and retrieve time-series data. The data schema is highly optimized for fast aggregations of similar time series to minimize storage space. Users of the TSD never need to access the underlying store directly. You can communicate with the TSD via a simple telnet-style protocol, an HTTP API or a simple built-in GUI. The first step in using OpenTSDB is to send time series data to the TSDs. A number of tools exist to pull data from various sources into OpenTSDB.

The beauty of the Canary Historian is that the same solution works as well on site as it does for the entire enterprise. You can log data locally, while sending it to your enterprise historian simultaneously. Best of all, as you grow, so does the solution. A single Canary Historian can log more than two million tags, and multiple Canary Historians can be clustered to handle tens of millions of tags. Enterprise historian solutions can be hosted in your own data centers or in AWS and Azure. And, unlike other enterprise historian solutions, Canary Historians don't require specialized teams of ten and more to maintain them. The Canary Historian is a NoSQL time series database that uses loss-less compression algorithms to provide you the best of both worlds, high-speed performance without requiring data interpolation!

TimescaleDB is the leading open-source relational database with support for time-series data. Fully managed or self‑hosted. Rely on the same PostgreSQL you know and love, with full SQL, rock-solid reliability, and a massive ecosystem. Write millions of data points per second per node. Horizontally scale to petabytes. Don’t worry about cardinality. Simplify your stack, ask more complex questions, and build more powerful applications. Spend less with 94-97% compression rates from best-in-class algorithms and other performance improvements. A modern, cloud-native relational database platform for time-series data based on TimescaleDB and PostgreSQL. The fast, easy, and reliable way to store all your time-series data. All observability data is time-series data. Efficiently finding and addressing infrastructure and application issues is a time-series problem.

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.

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.

Distributed Relational Database Service (DRDS) is a lightweight, flexible, stable, and efficient middleware product developed by Alibaba Cloud. DRDS focuses on expanding standalone relational databases, and has been tested by core transaction links in Tmall, such as during the Singles’ Day Shopping Festival. DRDS has been used for ten years and is a trusted database service provider. Supports cluster-based data read and write and data storage. DRDS operates on multiple standalone servers, and performance is not affected by the number of user connections. Supports upgraded and downgraded data configurations, and the visualized scale-up and scale-out of data storage. Provides read and write splitting to linearly improve the reading performance. Supports multiple data splitting methods based on data types, such as parallel data splitting. Focuses on the primary shards of the database and supports parallel query execution.

Blueflood is a high throughput, low latency, multi-tenant distributed metric processing system behind Rackspace Metrics, which is currently used in production by the Rackspace Monitoring team and Rackspace public cloud team to store metrics generated by their systems. In addition to Rackspace metrics, other large scale deployments of Blueflood can be found at community Wiki. Data from Blueflood can be used to construct dashboards, generate reports, graphs or for any other use involving time-series data. It focuses on near-realtime data, with data that is queryable mere milliseconds after ingestion. You send metrics to the ingestion service. You query your metrics from the Query service. And in the background, rollups are batch-processed offline so that queries for large time-periods are returned quickly.

Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, that combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is up to five times faster than standard MySQL databases and three times faster than standard PostgreSQL databases. It provides the security, availability, and reliability of commercial databases at 1/10th the cost. Amazon Aurora is fully managed by Amazon Relational Database Service (RDS), which automates time-consuming administration tasks like hardware provisioning, database setup, patching, and backups. Amazon Aurora features a distributed, fault-tolerant, self-healing storage system that auto-scales up to 64TB per database instance. It delivers high performance and availability with up to 15 low-latency read replicas, point-in-time recovery, continuous backup to Amazon S3, and replication across three Availability Zones.

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.

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.

The fully managed multi-cloud Postgres with a generous free tier. We separated storage and computing to offer autoscaling, branching, and bottomless storage. We separated storage and computing to make on-demand scalability possible. Compute activates on an incoming connection and scales to zero when not in use. Neon storage uses the "copy-on-write" technique to deliver data branching, online checkpointing, and point-in-time restore. This eliminates expensive full-data backup and restore operations required with traditional database-as-a-service systems. Neon allows you to instantly branch your Postgres database to support modern development workflows. You can create branches for test environments and for every deployment in your CI/CD pipeline. Our serverless architecture reduces computing and storage expenses. Specifically, Neon's autoscaling capabilities prevent over-provisioning and paying for under-utilized instances.

Deploy, monitor, provision and scale your favorite databases on AWS and Azure using Navisite’s fully managed database as a service (DBaaS) platform. With Navisite’s DBaaS, you get more than a powerful, high-speed service delivery platform. You get the expertise, services and scale you need to get ahead and stay ahead. Our fully managed DBaaS combines cloud management and automation with turnkey DBA services to reduce operating costs, speed time to market and simplify your journey to the cloud. Benefit from on-demand provisioning in the cloud, with seamless scaling and high availability via auto-failover on production-ready plans. Enable an additional layer of security with SSL-based access, and encrypt your data and backups "at-rest." Provision a database instantly, anywhere in the world, any time. Get scheduled and on-demand backups or snapshots with various restoration options for your data.

Webair provides Database-as-a-Service (DBaaS), a reliable and secure database management solution that gives your business simple, efficient and always available access to its mission-critical data. Our team has proven experience in managing the implementation, configuration, administration and optimization of database clusters, including business-critical, load-balanced and replicated MySQL clusters, including MariaDB, Galera and NoSQL. Webair’s Database Administrators are experts in helping you create a high-performance database environment. We work with you to design the best solution, matching the finest infrastructure to the right database configuration to meet your unique requirements. Free your business from routine database tasks such as performance monitoring, configuration, memory, storage and log file management, sizing, service pack upgrades and service patches. Focus on more important business aspects, including managing the critical data within your database.

Power your metrics and alerting with a leading open-source monitoring solution. Prometheus fundamentally stores all data as time series: streams of timestamped values belonging to the same metric and the same set of labeled dimensions. Besides stored time series, Prometheus may generate temporary derived time series as the result of queries. Prometheus provides a functional query language called PromQL (Prometheus Query Language) that lets the user select and aggregate time series data in real time. The result of an expression can either be shown as a graph, viewed as tabular data in Prometheus's expression browser, or consumed by external systems via the HTTP API. Prometheus is configured via command-line flags and a configuration file. While the command-line flags configure immutable system parameters (such as storage locations, amount of data to keep on disk and in memory, etc.). Download: https://sourceforge.net/projects/prometheus.mirror/

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

Riak® TS is the only enterprise-grade NoSQL time series database optimized specifically for IoT and Time Series data. It ingests, transforms, stores, and analyzes massive amounts of time series data. Riak TS is engineered to be faster than Cassandra. The Riak TS masterless architecture is designed to read and write data even in the event of hardware failures or network partitions. Data is evenly distributed across the Riak ring and, by default, there are three replicas of your data. This ensures at least one copy of your data is available for read operations. Riak TS is a distributed system with no central coordinator. It is easy to set up and operate. The masterless architecture makes it easy to add and remove nodes from a cluster. The masterless architecture of Riak TS makes it easy to add and remove nodes from your cluster. You can achieve predictable and near-linear scale by adding nodes using commodity hardware.

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.

KX Streaming Analytics provides the ability to ingest, store, process, and analyze historic and time series data to make analytics, insights, and visualizations instantly available. To help ensure your applications and users are productive quickly, the platform provides the full lifecycle of data services, including query processing, tiering, migration, archiving, data protection, and scaling. Our advanced analytics and visualization tools, used widely across finance and industry, enable you to define and perform queries, calculations, aggregations, machine learning and AI on any streaming and historical data. Deployable across multiple hardware environments, data can come from real-time business events and high-volume sources including sensors, clickstreams, radio-frequency identification, GPS systems, social networking sites, and mobile devices.

Parallel query engine with time- and symbol-indexed data access. Extended SQL syntax with advanced filtering and aggregations. Consolidate quotes, trades, snapshots, and reference data in one place. Strategy backtesting on high-frequency data. Quantitative and market microstructure research. Granular transaction cost analysis and rollup reporting. Market surveillance and anomaly detection. Non-transparent ETF/ETN decomposition. FAST, SBE, and proprietary protocols. Plain text protocol. Consolidated and direct feeds. Built-in latency monitoring tools. End-of-day archives. ETL from institutional and retail financial data platforms. Parallel SQL engine with syntax extensions. Advanced filtering by trading session, auction stage, index composition. Optimized aggregates for OHLCV and VWAP calculations. Interactive SQL console with auto-completion. API endpoint for programmatic integration. Scheduled SQL reporting with email, file, and web delivery. JDBC and ODBC drivers.

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.

CockroachDB: Cloud-native, distributed SQL. Your cloud applications deserve a cloud-native database. Cloud-based apps and services deserve a database that scales across clouds, eases operational complexity, and improves reliability. CockroachDB delivers resilient, distributed SQL with ACID transactions and data partitioned by location. Automate operations for mission-critical applications by pairing CockroachDB with orchestration tools like Kubernetes and Mesosphere DC/OS. Every node can service both reads and writes so that you can scale query throughput and database capacity by simply adding more endpoints. Just add new nodes to CockroachDB, and it automatically rebalances data, completely removing the pain of manual sharding. As demand shifts, CockroachDB detects hotspots and intelligently distributes data to maintain performance. Tune your database at the row level so that data lives close to your users and you can minimize query latency.

Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads. As a document database, Amazon DocumentDB makes it easy to store, query, and index JSON data. Amazon DocumentDB is a non-relational database service designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data. Amazon DocumentDB is designed for 99.99% availability and replicates six copies of your data across three AWS Availability Zones (AZs).

TencentDB for MySQL makes it easy for you to deploy and use MySQL database, one of the world's most popular open source relational database, in the cloud. TencentDB for MySQL is cost-efficient and flexible; it only takes minutes to deploy a scalable MySQL database instance and you can resize your hardware capacity without shutting down your machines. It comes with a full set of streamlined database OPS solutions, including backups, rollbacks, monitoring, fast scaling and data transfer, freeing you up to focus your energies on developing your business. You can launch and connect to a production-ready MySQL database in minutes with just a few clicks in the TencentDB for MySQL console. TencentDB for MySQL comes with preset parameters and settings tailored for your server, and you can further refine and customize your MySQL database settings via the database parameter group.

Fully managed and hosted PostgreSQL with high performance and all the extensions you want out of the box. Set up fully managed PostgreSQL in less than 10 minutes — directly from our web console or programmatically via our API, CLI, Terraform provider or Kubernetes operator. Our stand-by nodes act automatically as read replicas, and you can also create additional read replicas in different public clouds and regions, even building multi-cloud architectures. Our Point-In-Time-Recovery lets you restore your data to any time within your selected retention period. A fully managed SQL relational database, deployable in the cloud of your choice. Known for reliability, a robust set of features, and exceptionally high performance. Fits well for almost any case, such as creating location-based services, mission critical business applications or simply as a general transactional database.

The Leading High-Performance Distributed SQL Database. Open source, cloud native relational DB for powering global, internet-scale apps. Single-Digit Millisecond Latency Build blazing fast cloud applications by serving queries directly from the DB. Massive Scale. Achieve millions of transactions per second and store multiple TB’s of data per node. Geo-Distribution. Deploy across regions and clouds with synchronous or multi-master replication. Built for Cloud Native Architectures. Develop, deploy and operationalize modern applications faster than ever before with YugabyteDB. Gain Developer Agility. Leverage full power of PostgreSQL-compatible SQL and distributed ACID transactions. Operate Resilient Services. Ensure continuous availability even when underlying compute, storage or network fails. Scale On-Demand. Add and remove nodes at will. Say no to over-provisioned clusters forever. Lower User Latency.

Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra–compatible database service. With Amazon Keyspaces, you can run your Cassandra workloads on AWS using the same Cassandra application code and developer tools that you use today. You don’t have to provision, patch, or manage servers, and you don’t have to install, maintain, or operate software. Amazon Keyspaces is serverless, so you pay for only the resources you use and the service can automatically scale tables up and down in response to application traffic. You can build applications that serve thousands of requests per second with virtually unlimited throughput and storage. Amazon Keyspaces gives you the performance, elasticity, and enterprise features you need to operate business-critical Cassandra workloads at scale. Process data at high speeds for applications that require single-digit-millisecond latency, such as industrial equipment maintenance, trade monitoring, etc.

Data can be pushed in KairosDB via multiple protocols like Telnet, Rest and Graphite. Other mechanisms such as plugins can also be used. KairosDB stores time series in Cassandra, the popular and performant NoSQL datastore. The schema consists of 3 column families. This API provides operations to list existing metric names, list tag names and values, store metric data points, and query for metric data points. With a default install, KairosDB serve up a query page whereby you can query data within the data store. It's designed primarily for development purposes. Aggregators perform an operation on data points and down samples. Standard functions like min, max, sum, count, mean and more are available. Import and export is available on the KairosDB server from the command line. Internal metrics to the data store can monitor the server’s performance.

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.

VictoriaMetrics Cloud allows users to run the Enterprise version of VictoriaMetrics, hosted on AWS, without the need to perform typical DevOps tasks such as proper configuration, monitoring, log collection, access protection, software updates, and backups. We run VictoriaMetrics Cloud instances in our environment on AWS and provide easy-to-use endpoints for data ingestion and querying. The VictoriaMetrics team takes care of optimal configuration and software maintenance. It comes with the following features: It can be used as a Managed Prometheus - configure Prometheus or Vmagent to write data to Managed VictoriaMetrics and then use the provided endpoint as a Prometheus data source in Grafana; Every VictoriaMetrics Cloud instance runs in an isolated environment, so instances cannot interfere with each other; VictoriaMetrics Cloud instance can be scaled up or scaled down in a few clicks; Automated backups;

Warp 10 is a modular open source platform that collects, stores, and analyzes data from sensors. Shaped for the IoT with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 is both a time series database and a powerful analytics environment, allowing you to make: statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The analysis environment can be implemented within a large ecosystem of software components such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. It can also access data stored in many existing solutions, relational or NoSQL databases, search engines and S3 type object storage system.

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.

It's performance, superior features and unmatched functionality have led OneTick Database to be embraced by leading banks, brokerages, data vendors, exchanges, hedge funds, market makers and mutual funds. OneTick is the premier enterprise-wide solution for tick data capture, streaming analytics, data management and research. With its superior features and unmatched functionality, OneTick is being embraced enthusiastically by leading hedge funds, mutual funds, banks, brokerages, market makers, data vendors and exchanges. OneTick’s proprietary time series database is a unified, multi-asset class platform that includes a fully integrated streaming analytics engine and built-in business logic to eliminate the need for multiple disparate systems. The system provides the lowest total cost of ownership available.

Cortex is an open source project that adds horizontal scalability. While Prometheus can scale up to 1 million samples/sec on a single machine, with Cortex horizontal scalability is practically limitless. In a constantly changing environment, you need alternative approaches to monitoring individual VMs or servers. Prometheus' service-discovery driven pull-based metrics system was designed for the dynamic nature of microservices. It lets you easily monitor your whole environment no matter how many moving parts. Instrument your application to create custom metrics using standard Prometheus client libraries, or take advantage of the extensive collection of Prometheus Exporters that collect data from existing applications like MySQL, Redis, Java, ElasticSearch and many more.

Azure Cosmos DB is a fully managed NoSQL database service for modern app development with guaranteed single-digit millisecond response times and 99.999-percent availability backed by SLAs, automatic and instant scalability, and open source APIs for MongoDB and Cassandra. Enjoy fast writes and reads anywhere in the world with turnkey multi-master global distribution. Reduce time to insight by running near-real time analytics and AI on the operational data within your Azure Cosmos DB NoSQL database. Azure Synapse Link for Azure Cosmos DB seamlessly integrates with Azure Synapse Analytics without data movement or diminishing the performance of your operational data store.

Couchbase Capella is a cloud database platform that optimizes data storage and processing for both JSON-native operational and analytical data. A faster, better DBaaS for transaction, search, AI, and edge applications, with real-time analytics. Start easily with Capella by using SQL to query your JSON data, and get natural language coding assistance from Capella iQ. Capella is a multipurpose database supporting operational and analytic workloads and use cases, including JSON analytics, vector search, and mobile synchronization. It delivers millisecond response at scale, with the best price-performance of any document Database-as-a-Service. Try for free today and be up and running in minutes. Whether you're tackling development, architectural, or deployment challenges, there are many great reasons to future-proof with Capella.

Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Amazon Neptune supports popular graph models Property Graph and W3C's RDF, and their respective query languages Apache TinkerPop Gremlin and SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security. Proactively detect and investigate IT infrastructure using a layered security approach. Visualize all infrastructure to plan, predict and mitigate risk. Build graph queries for near-real-time identity fraud pattern detection in financial and purchase transactions.

Amazon SimpleDB is a highly available NoSQL data store that offloads the work of database administration. Developers simply store and query data items via web services requests and Amazon SimpleDB does the rest. Unbound by the strict requirements of a relational database, Amazon SimpleDB is optimized to provide high availability and flexibility, with little or no administrative burden. Behind the scenes, Amazon SimpleDB creates and manages multiple geographically distributed replicas of your data automatically to enable high availability and data durability. The service charges you only for the resources actually consumed in storing your data and serving your requests. You can change your data model on the fly, and data is automatically indexed for you. With Amazon SimpleDB, you can focus on application development without worrying about infrastructure provisioning, high availability, software maintenance, schema and index management, or performance tuning.

Datastore is a highly scalable NoSQL database for your applications. Datastore automatically handles sharding and replication, providing you with a highly available and durable database that scales automatically to handle your applications' load. Datastore provides a myriad of capabilities such as ACID transactions, SQL-like queries, indexes, and much more. With Datastore's RESTful interface, data can easily be accessed by any deployment target. You can build solutions that span across App Engine and Compute Engine and rely on Datastore as the integration point. Focus on building your applications without worrying about provisioning and load anticipation. Datastore scales seamlessly and automatically with your data, allowing applications to maintain high performance as they receive more traffic.

IBM Db2 is a family of data management products, including the Db2 relational database. The products feature AI-powered capabilities to help you modernize the management of both structured and unstructured data across on-premises and multicloud environments. By helping to make your data simple and accessible, the Db2 family positions your business to pursue the value of AI. Most of the Db2 family is available on the IBM Cloud Pak® for Data platform, either as an add-on or an included data source service, making virtually all of your data available across hybrid or multicloud environments to fuel your AI applications. Easily converge your transactional data stores and rapidly derive insights through universal, intelligent querying of data across disparate sources. Cut costs with the multimodel capability that eliminates the need for data replication and migration. Enhance agility by running Db2 on any cloud vendor.

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.

Tessell makes deploying cloud databases extremely simple and elegant. Our fully-managed database service takes care of your data infrastructure and data management needs. Turn high-performance computing into durable, zero data loss infrastructure. Give your database enterprise-grade data protection with multi-AZ HA, cross-region DR, and BCP. Policy-driven consumer-grade data management for Prod, UAT, QA, Dev in one place. Hosted and managed by Tessell. In a few simple steps, create a fully-managed database service in under 10 minutes. Bring your own data or deploy the sample data, and enjoy the data apps. Modernize your databases in one click with Tessell. Get the best performance while being very cost-effective. Protect your production database with continuous backup of transactional data and logs. Create and store all kinds of data, including table dumps and anonymized data, for secondary environments.