Search Results for "time series analisys"
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Showing 39 open source projects for "time series analisys"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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TimescaleDB
An open-source time-series SQL database optimized for fast ingest
TimescaleDB is the open-source relational database for time-series and analytics. Build powerful data-intensive applications. Become instantly productive with full SQL. Rely on the same PostgreSQL you know, love, and trust. Hyperfunctions make time series easier. Achieve 10-100x faster queries than with vanilla PostgreSQL, InfluxDB, MongoDB. Write millions of data points per second per node. -
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GreptimeDB
An open-source, cloud-native, unified time series database for metrics
GreptimeDB treats all time series as contextual events with timestamps, and thus unifies the processing of metrics, logs, and events. It supports analyzing metrics, logs, and events with SQL, PromQL, and streaming with continuous aggregation. GreptimeDB is a time-series database optimized for storing and querying large amounts of time-series data, commonly used in monitoring and IoT applications. -
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TDengine
Open-source time-series database with high-performance and scalability
...In addition, this feature is open source. TDengine uses SQL as the query language, thereby reducing learning and migration costs, while adding SQL extensions to handle time-series data better, and supporting convenient and flexible schemaless data ingestion. -
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GridDB
GridDB is a next-generation open source database
A cyber-physical systems is a system that collects a variety of data in physical space (the real world), analyzes and converts it into knowledge in cyberspace, and feeds the knowledge back to the real world to revitalize industry and solve social problems. GridDB is an open database that enables real-time processing of vast amounts of time-series data in physical space, which is necessary to realize a cyber-physical system. Multi-model architecture capable of supporting various data stores with time-series data-oriented and pluggable data stores for efficient real-time processing and management of huge amounts of time-series data at high frequency. ... -
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Cloudberry
One advanced and mature open-source MPP
Apache Cloudberry is a distributed real-time analytics engine designed for querying massive social media datasets. It integrates with Apache AsterixDB and supports efficient ad-hoc queries and aggregations across large volumes of data. Cloudberry is especially useful for dashboards, trend analysis, and time-series social data exploration. -
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VictoriaMetrics
VictoriaMetrics: fast, cost-effective monitoring solution
VictoriaMetrics is a fast, cost-effective and scalable monitoring solution and time series database. VictoriaMetrics is available in binary releases, Docker images, Snap packages and source code. Just download the latest version of VictoriaMetrics. VictoriaMetrics is developed at a fast pace, so it is recommended periodically checking the CHANGELOG and performing regular upgrades. It can be used as long-term storage for Prometheus. -
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CrateDB
CrateDB is a distributed and scalable SQL database
CrateDB is a distributed SQL database designed for massive machine data and real-time analytics. It combines the scalability and performance of NoSQL with the power and simplicity of SQL, allowing for horizontal scaling, full-text search, and complex queries over large datasets. Built in Java and powered by Elasticsearch and Lucene, CrateDB is optimized for high-velocity data ingestion and dynamic queries. -
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Stoolap
A Modern Embedded SQL Database written in Rust
Stoolap is a lightweight, self-hosted analysis and visualization tool designed to help developers and operations teams explore log data, metrics, and debugging information from distributed systems or local applications. Instead of relying on heavy commercial observability platforms, stoolap provides a fast, focused interface where users can filter, query, and visualize time-series data, logs, traces, and error metrics in a cohesive environment. Its intuitive query builder lets users craft powerful filters and aggregations without complex configurations, making it easier to diagnose performance bottlenecks or uncover unusual events during testing and production. Stoolap supports dashboards, alert triggering, and exports so teams can embed visualizations in reports or monitor critical thresholds in real time. -
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QuestDB
An open source SQL database designed to process time series data
...It includes endpoints for PostgreSQL wire protocol, high-throughput schema-agnostic ingestion using InfluxDB Line Protocol, and a REST API for queries, bulk imports, and exports. QuestDB implements ANSI SQL with native extensions for time-oriented language features. These extensions make it simple to correlate data from multiple sources using relational and time series joins. QuestDB achieves high performance from a column-oriented storage model, massively-parallelized vector execution, SIMD instructions, and various low-latency techniques. The entire codebase was built from the ground up in Java and C++, with no dependencies, and is 100% free from garbage collection. ... -
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KCloud‑Platform‑IoT
KCloud-Platform-IoT
KCloud-Platform-IoT is a comprehensive open-source IoT management platform built with Spring Cloud and Vue.js. It supports device registration, data collection, rule-based processing, and dashboard visualization. Designed for scalability and modularity, the platform is ideal for managing large IoT fleets in industrial or smart city environments. -
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Prometheus
Open source monitoring system and time series database
Prometheus is a leading open source systems and service monitoring solution. It works by collecting metrics from configured targets at given intervals, evaluating rule expressions, and then displaying the results. It can also signal an alert if a condition is observed to be true. What sets Prometheus apart from other monitoring systems is its highly dimensional data model, powerful query language, autonomous single server nodes, among many other distinguishing features. It also offers... -
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EventStoreDB
The stream database optimised for event sourcing
...It was built from the ground up for Event Sourcing, we believe that makes it the best solution in the market for building event-sourced systems. Event Sourcing offers some great benefits over state-oriented systems; the key ones are explained below. An event-sourced system stores your data as a series of immutable events over time, providing one of the strongest audit log options available. All state changes are kept, so it is possible to move systems backward and forwards in time which is extremely valuable for debugging and “what if” analysis. -
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pgai
A suite of tools to develop RAG, semantic search, and other AI apps
pgai is a suite of PostgreSQL extensions developed by Timescale to empower developers in building AI applications directly within their databases. It integrates tools for vector storage, advanced indexing, and AI model interactions, facilitating the development of applications like semantic search and Retrieval-Augmented Generation (RAG) without leaving the SQL environment. -
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ObjectBox Java Database
Java and Android Database - fast and lightweight without any ORM
High-performance NoSQL database with integrated Data Sync for decentralized Edge Computing. Get fast access to the data you need across Embedded Devices, IoT, and Mobile. ObjectBox is 10x faster than any alternative, with high-speed data ingestion that increases response times. Check out our benchmarks. ObjectBox’ out-of-the-box synchronization makes data available when needed where needed, eliminating data islands and improving data flow. Develop applications that work on- and offline,... -
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LinDB
LinDB is a scalable, high performance, high availability database
LinDB is a scalable, high-performance, high-availability distributed time series database. A single server could easily support more than one million write TPS; With fundamental techniques like efficient compression storage and parallel computing, LinDB delivers highly optimized query performance. The multi-channel replication protocol supports any amount of nodes, and ensures the system's availability. -
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Citus
Distributed PostgreSQL as an extension
Citus is a PostgreSQL extension that transforms Postgres into a distributed database, so you can achieve high performance at any scale. With Citus, you extend your PostgreSQL database with new superpowers. Distributed tables are sharded across a cluster of PostgreSQL nodes to combine their CPU, memory, storage and I/O capacity. References tables are replicated to all nodes for joins and foreign keys from distributed tables and maximum read performance. Distributed query engine routes and... -
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Cortex
A horizontally scalable, multi-tenant, long term Prometheus
...Durably store data for longer than the lifetime of any single machine, and use this data for long-term capacity planning. Cortex makes your PromQL queries blazin' fast through aggressive parallelization and caching. Cortex gives you a global view of Prometheus time series data that includes data in long-term storage, greatly expanding the usefulness of PromQL for analytical purposes. Cortex runs across multiple machines in a cluster, exceeding the throughput and storage of a single machine. This enables you to send the metrics from multiple Prometheus servers to a single Cortex cluster. -
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ArcticDB
ArcticDB is a high performance, serverless DataFrame database
Built for the modern Python Data Science ecosystem, ArcticDB transforms your ability to handle complex real-world data with an Incredibly fast proven Petabyte scale. ArcticDB is designed with quant users in mind. It allows you to self-manage your data leveraging your preferred infrastructure. Giving you the keys to protect your most valuable asset. Supports large concurrent writes to many tables ensuring datasets can be onboarded fast and in the most convenient format. Scale-out architecture... -
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MatrixOne
Hyperconverged cloud-edge native database
MatrixOne is a future-oriented hyperconverged cloud & edge native DBMS that supports transactional, analytical, and streaming workload with a simplified and distributed database engine, across multiple data centers, clouds, edges and other heterogeneous infrastructures. A monolithic database engine is designed to support hybrid workloads: transactional, analytical, streaming, time-series, machine learning, etc. MatrixOne supports seamless workload migration and bursting among different locations and infrastructures. MatrixOne provides industry-leading latency control with optimized consistency protocol. Accelerated queries supported by patented vectorized execution as well as optimal computation push-down strategies through factorization techniques. ... -
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DataScript
Immutable database and Datalog query engine for Clojure, ClojureScript
An immutable in-memory database and Datalog query engine in Clojure and ClojureScript. DataScript is meant to run inside the browser. It is cheap to create, quick to query and ephemeral. You create a database on page load, put some data in it, track changes, do queries and forget about it when the user closes the page. DataScript databases are immutable and based on persistent data structures. In fact, they’re more like data structures than databases (think Hashmap). Unlike querying a real... -
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CursusDB
CursusDB is an open-source distributed in-memory database
CursusDB is a time-series database built for high-performance analytics and data processing, optimized for handling large volumes of sequential data efficiently. -
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Arctic TimeSeries and Tick store
High performance datastore for time series and tick data
Arctic is a timeseries/dataframe database that sits atop MongoDB. Arctic supports serialization of a number of datatypes for storage in the mongo document model. Serializes a number of data types eg. Pandas DataFrames, Numpy arrays, Python objects via pickling etc. so you don't have to handle different datatypes manually. Uses LZ4 compression by default on the client side to get big savings on network / disk. Allows you to version different stages of an object and snapshot the state (In some... -
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FiloDB
Distributed Prometheus time series database
FiloDB is an open-source distributed, real-time, in-memory, massively scalable, multi-schema time series / event / operational database with Prometheus query support and some Spark support as well. The normal configuration for real-time ingestion is deployment as stand-alone processes in a cluster, ingesting directly from Apache Kafka. The processes form a cluster using peer-to-peer Akka Cluster technology. -
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OpenTSDB
A scalable, distributed time series database
OpenTSDB is a distributed, scalable Time Series Database (TSDB) written on top of HBase. OpenTSDB was written to address a common need: store, index and serve metrics collected from computer systems (network gear, operating systems, applications) at a large scale, and make this data easily accessible and graphable. Store and serve massive amounts of time series data without losing granularity. -
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KairosDB
Fast scalable time series database
KairosDB is a fast distributed scalable time series database written on top of Cassandra.
