QuestDB is an open-source NewSQL relational database designed to process time-series data, faster. QuestDB ingests data via HTTP, PostgresSQL wire protocol, Influx line protocol or directly from Java. Reading data is done using SQL via HTTP, PostgreSQL wire protocol or via Java API. The whole database and console fits in a 3.5Mb package.
https://www.questdb.io/Tags | database time-series-database time-series sql relational-database analytics real-time-analytics |
Implementation | Java |
License | Apache |
Platform | OS-Independent |
InfluxDB is an open source time series platform. This includes APIs for storing and querying data, processing it in the background for ETL or monitoring and alerting purposes, user dashboards, and visualizing and exploring the data and more. The master branch on this repo now represents the latest InfluxDB, which now includes functionality for Kapacitor (background processing) and Chronograf (the UI) all in a single binary. It is designed to handle high write and query loads and provides a SQL-like query language called InfluxQL for interacting with data.
database time-series metrics time-series-database analytics real-time-analytics monitoringTimescaleDB is an open-source database designed to make SQL scalable for time-series data. It is engineered up from PostgreSQL, providing automatic partitioning across time and space (partitioning key), as well as full SQL support. TimescaleDB is packaged as a PostgreSQL extension and released under the Apache 2 open-source license.
time-series-database postgresql time-series sql postgres tsdb iot financial-analysis analytics database postgresql-extensionDruid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations. Druid can load both streaming and batch data.
analytics column-store time-series time-series-database aggregation no-sqlLinDB is an open-source Time Series Database which provides high performance, high availability and horizontal scalability. LinDB takes a lot of best practice of TSDB and implements some optimizations based on the characteristics of time series data. Unlike writing a lot of Continuous-Query for InfluxDB, LinDB supports rollup in specific interval automatically after creating the database. Moreover, LinDB is extremely fast for parallel querying and computing of distributed time series data.
time-series-database database monitoring metrics high-performance multi-active-idcs-native distributed-databaseVoltDB was specifically designed for contemporary software applications that are pushed beyond their limits by high volume data sources. VoltDB provides the ability to capture, store and process incoming data at millions of read/write operations per second. And VoltDB’s relational model opens that data to be analyzed in real-time, using familiar Business Intelligence tools, to identify data patterns and trends, spot anomalies, or perform tracking and alerting.
database relational acid bigdata scale-out distributed distributed-database oltp analyticsSiriDB is a highly-scalable, robust and super fast time series database. Build from the ground up SiriDB uses a unique mechanism to operate without indexes and allows server resources to be added on the fly. SiriDB's unique query language includes dynamic grouping of time series for easy and super fast analysis over large amount's of time series.
time-series-database database time-series analyticsInfluxDB is an open-source, distributed, time series database with no external dependencies. It's useful for recording metrics, events, and performing analytics. Everything in InfluxDB is a time series that you can perform standard functions on like min, max, sum, count, mean, median, percentiles, and more. Collect your data on any interval and compute rollups on the fly later.
monitoring graph scalable time-series time-series-database databaseKairosDB is a fast distributed scalable time series database written on top of Cassandra. Data can be pushed in KairosDB via multiple protocols : Telnet, Rest, Graphite. KairosDB stores time series in Cassandra, the popular and performant NoSQL datastore. It supports aggregators which can perform an operation on data points and down samples. Standard functions like min, max, sum, count, mean etc.
time-series-database database analytics aggregation time-seriesDalmatinerDB is a metric database written in pure Erlang. It takes advantage of some special properties of metrics to make some tradeoffs. Its goal is to make a store for metric data (time, value of a metric) that is fast, has a low overhead, and is easy to query and manage. DalmatinerDB allows for metric input in second or even sub-second precision. It will interpolate the missing values to the best of it’s abilities. This is usually acceptable for aggregated data.
time-series-database database time-series analytics metrics nosqlClickHouse is an open source column-oriented database management system capable of real time generation of analytical data reports using SQL queries. It is Linearly Scalable, Blazing Fast, Highly Reliable, Fault Tolerant, Data compression, Real time query processing, Web analytics, Vectorized query execution, Local and distributed joins. It can process hundreds of millions to more than a billion rows and tens of gigabytes of data per single server per second.
database columnar-database column-oriented columnar analytics real-time big-dataAkumuli is a time-series database for modern hardware. It can be used to capture, store and process time-series data in real-time. The word "akumuli" can be translated from Esperanto as "accumulate".
time-series database c-plus-plus tsdb time-series-database metrics column-oriented columnar-databasePinot is a realtime distributed OLAP datastore, which is used at LinkedIn to deliver scalable real time analytics with low latency. It can ingest data from offline data sources (such as Hadoop and flat files) as well as online sources (such as Kafka). Pinot is designed to scale horizontally, so that it can scale to larger data sets and higher query rates as needed.
olap-database olap analytics realtime-analytics columnar-database distributed column-storeTrailDB is a library, implemented in C, which allows you to query series of events at blazing speed. TrailDB is also optimized for speed of development: Use its simple API with your favorite language, in your favorite environment. TrailDB's secret sauce is data compression. It leverages predictability of time-based data to compress your data to a fraction of its original size. In contrast to traditional compression, you can query the encoded data directly, decompressing only the parts you need.
database data-analytics event-data big-data time-series time-series-databaseUse Cases documentation demonstrates solutions to real-world data problems using Axibase Time Series Database (ATSD) and contains in-depth guides for programmatic integration with commonly-used enterprise software systems and services, as well as tutorials for data transformation and visualizations created with ATSD. Interactive visualizations tracking interesting datasets from a variety of sources.
dataset axibase atsd socrata open-data time-series statistical-analysis database visualization time-series-database time-series-analysisGnocchi is an open-source |time series| database. The problem that Gnocchi solves is the storage and indexing of |time series| data and resources at a large scale. This is useful in modern cloud platforms which are not only huge but also are dynamic and potentially multi-tenant. Gnocchi takes all of that into account. Gnocchi has been designed to handle large amounts of aggregates being stored while being performant, scalable and fault-tolerant. While doing this, the goal was to be sure to not build any hard dependency on any complex storage system.
timeseries timeseries-database gnocchi time-series-database time-series database aggregationAtlas was developed by Netflix to manage dimensional time series data for near real-time operational insight. Atlas features in-memory data storage, allowing it to gather and report very large numbers of metrics, very quickly. Atlas captures operational intelligence. Whereas business intelligence is data gathered for analyzing trends over time, operational intelligence provides a picture of what is currently happening within a system.
time-series-database database time-series metrics in-memoryGeoMesa is an open-source, distributed, spatio-temporal database built on a number of distributed cloud data storage systems, including Accumulo, HBase, Cassandra, and Kafka. Leveraging a highly parallelized indexing strategy, GeoMesa aims to provide as much of the spatial querying and data manipulation to Accumulo as PostGIS does to Postgres.
database geospatial-database spatial-database geospatial geospatial-analytics mapsOpenTSDB is a Classical time series database on top of HBase. Now support Cassandra and Bigtable. BTrDB (Berkeley Tree Database) is a High performance time series database designed to support high density data storage applications.
awesome time-series database tsdb monitoring metrics awesome-list distributed-systemsGraphite is an enterprise-scale monitoring tool that runs well on cheap hardware. It is a highly scalable real-time graphing system. It stores numeric time-series data and renders graphs of this data on demand.
monitoring graph scalable time-series time-series-database databaseTimely is a time series database application that provides secure access to time series data. Timely is written in Java and designed to work with Apache Accumulo and Grafana.
accumulo time-series-database time-series database
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