Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

Prometheus - Service Monitoring System and Time Series Database

Fast, concurrent, evicting in-memory cache written to keep big number of entries without impact on performance. BigCache keeps entries on heap but omits GC for them. To achieve that operations on bytes arrays take place, therefore entries (de)serialization in front of the cache will be needed in most use cases. 

bigcache - Efficient cache for gigabytes of data written in Go.

CockroachDB is a cloud-native SQL database for building global, scalable cloud services that survive disasters.CockroachDB is a distributed SQL database built on a transactional and strongly-consistent key-value store. It scales horizontally; survives disk, machine, rack, and even datacenter failures with minimal latency disruption and no manual intervention; supports strongly-consistent ACID transactions; and provides a familiar SQL API for structuring, manipulating, and querying data.
 
CockroachDB supports the PostgreSQL wire protocol, so you can use any available PostgreSQL client drivers.

CockroachDB is a cloud-native SQL database for building global, scalable cloud services that survive disasters.CockroachDB is a distributed SQL database built on a transactional and strongly-consistent key-value store. It scales horizontally; survives disk, machine, rack, and even datacenter failures with minimal latency disruption and no manual intervention; supports strongly-consistent ACID transactions; and provides a familiar SQL API for structuring, manipulating, and querying data.

CockroachDB - Cloud-native SQL database.

PouchDB is an open-source JavaScript database inspired by Apache CouchDB that is designed to run well within the browser. PouchDB was created to help web developers build applications that work as well offline as they do online. It enables applications to store data locally while offline, then synchronize it with CouchDB and compatible servers when the application is back online, keeping the user's data in sync no matter where they next login.

PouchDB - The Javascript Database that Syncs

LinDB 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.
 
LinDB supports Metric + Tags + Fields, and is schema-free; The LinQL is handy for realtime data analytics. Tags based sharding strategy in LinDB solves the hotspots problem, and is truly horizontally expanded available by simply adding new broker and storage nodes.

LinDB 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.


Lindb - Distributed Time Series Database

Nebula Graph is an open-source graph database capable of hosting super large-scale graphs with billions of vertices (nodes) and trillions of edges, with milliseconds of latency. It delivers enterprise-grade high performance to simplify the most complex data sets imaginable into meaningful and useful information. 
 
Nebula Graph is Symmetrically distributed, Separates Storage and computation, Horizontal scalability, Strong data consistency by RAFT protocol, Role-based access control for higher level security and lot more.

Nebula Graph is an open-source graph database capable of hosting super large-scale graphs with billions of vertices (nodes) and trillions of edges, with milliseconds of latency. It delivers enterprise-grade high performance to simplify the most complex data sets imaginable into meaningful and useful information. 

Nebula Graph - A distributed, scalable, lightning-fast graph database

MapDB is an embedded database engine. It provides Maps and other collections backed by disk or memory storage. It offers excellent performance comparable to java collections, but is not limited by GC overhead. It is also a full database engine with storage backends, transactions, cache algorithms, expiration and many other options. MapDB provides concurrent Maps, Sets and Queues backed by disk storage or off-heap memory. 

MapDB - Embedded Database Engine

VictoriaMetrics is a fast, cost-effective and scalable monitoring solution and time series database. VictoriaMetrics can be used as long-term storage for Prometheus or for vmagent. It supports Prometheus querying API, so it can be used as Prometheus drop-in replacement in Grafana. It implements MetricsQL query language backwards compatible with PromQL. 
 
VictoriaMetrics provides global query view. Multiple Prometheus instances or any other data sources may ingest data into VictoriaMetrics. Later this data may be queried via a single query.

VictoriaMetrics is a fast, cost-effective and scalable monitoring solution and time series database. VictoriaMetrics can be used as long-term storage for Prometheus or for vmagent. It supports Prometheus querying API, so it can be used as Prometheus drop-in replacement in Grafana. It implements MetricsQL query language backwards compatible with PromQL. 

VictoriaMetrics - Fast, cost-effective and scalable monitoring solution and time series database

immudb is a database with built-in cryptographic proof and verification. It can track changes in sensitive data and the integrity of the history will be protected by the clients, without the need to trust the server. It can operate as a key-value store or as relational database (SQL).
 
Traditional database transactions and logs are hard to scale and are mutable, so there is no way to know for sure if your data has been compromised. immudb is immutable. You can add new versions of existing records, but never change or delete records. This lets you store critical data without fear of it being changed silently.
 
Data stored in immudb is cryptographically coherent and verifiable, just like blockchains, but without all the complexity. Unlike blockchains, immudb can handle millions of transactions per second, and can be used both as a lightweight service or embedded in your application as a library. Companies use immudb to protect credit card transactions and to secure processes by storing digital certificates and checksums.

immudb is a database with built-in cryptographic proof and verification. It can track changes in sensitive data and the integrity of the history will be protected by the clients, without the need to trust the server. It can operate as a key-value store or as relational database (SQL).

immudb - world’s fastest immutable database

SeaORM is a relational ORM to help you build light weight and concurrent web services in Rust. Relying on SQLx, SeaORM is a new library with async support from day 1. It allows you to build complex queries without 'fighting the ORM'.



SeaORM -  An async & dynamic ORM for Rust

Sensei is a distributed data system that was built to support many product initiatives at LinkedIn, including the real-time faceted search in <A HREF="http://www.linkedin.com/signal/" target="_blank">LinkedIn Signal</A> and the news feed and tabs on the Homepage. Sensei is both a search engine and a database. It is designed to query and navigate through documents that consist of unstructured text and well-formed and structured metadata. 
 It supports Fast realtime updates, Complex query language and REST/JSON api, Hadoop integration and lot more.

Sensei is a distributed data system that was built to support many product initiatives at LinkedIn, including the real-time faceted search in LinkedIn Signal and the news feed and tabs on the Homepage. Sensei is both a search engine and a database. It is designed to query and navigate through documents that consist of unstructured text and  well-formed and structured metadata. Sensei is both a search engine and a database.

SenseiDB - Distributed, Realtime, Semi-Structured Database from LinkedIn

Cloudata is Distributed Large scale Structured Data Storage, and open source project implementing Google's Bigtable. It's DBMS(Database Management System), but not Relational DBMS. It can store more than Peta bytes.

Cloudata - Structured Data Storage implementing Google's Bigtable.

Copycat is a fault-tolerant state machine replication framework. Built on the Raft consensus algorithm, it handles replication and persistence and enforces strict ordering of inputs and outputs, allowing developers to focus on single-threaded application logic. Its event-driven model allows for efficient client communication with replicated state machines, from simple key-value stores to wait-free locks and leader elections. You supply the state machine and Copycat takes care of the rest, making it easy to build robust, safe distributed systems.


Copycat - A novel implementation of the Raft consensus algorithm

MarketStore is a database server optimized for financial timeseries data. You can think of it as an extensible DataFrame service that is accessible from anywhere in your system, at higher scalability. It is designed from the ground up to address scalability issues around handling large amounts of financial market data used in algorithmic trading backtesting, charting, and analyzing price history with data spanning many years, including tick-level for the all US equities or the exploding crypto currencies space. If you are struggling with managing lots of HDF5 files, this is perfect solution to your problem.
 
The batteries are included so you can start pulling crypto price data from GDAX right after you install MarketStore. Then you can query DataFrame content over the network at as low latency as your local HDF5 files from disk, and appending new data to the end is two orders of magnitude faster than DataFrame would be. This is because the storage format is optimized for the type of data and use cases as well as for modern filesystem/hardware characteristics.

 MarketStore is a database server optimized for financial timeseries data. You can think of it as an extensible DataFrame service that is accessible from anywhere in your system, at higher scalability. It is designed from the ground up to address scalability issues around handling large amounts of financial market data used in algorithmic trading backtesting, charting, and analyzing price history with data spanning many years, including tick-level for the all US equities or the exploding crypto currencies space. If you are struggling with managing lots of HDF5 files, this is perfect solution to your problem.

Marketstore - DataFrame Server for Financial Timeseries Data

Elassandra is a fork of Elasticsearch modified to run as a plugin for Apache Cassandra in a scalable and resilient peer-to-peer architecture. Elasticsearch code is embedded in Cassanda nodes providing advanced search features on Cassandra tables and Cassandra serve as an Elasticsearch data and configuration store. It supports Cassandra vnodes and scales horizontally by adding more nodes.
 
Elassandra supports Full-text search, Spatial search, Real-time aggregation on your Cassandra data. Elassandra is a sharded multi-master database, where Elasticsearch is sharded master-slave, Thus, Elassandra has no Single Point Of Write, helping to achieve high availability.

Elassandra is a fork of Elasticsearch modified to run as a plugin for Apache Cassandra in a scalable and resilient peer-to-peer architecture. Elasticsearch code is embedded in Cassanda nodes providing advanced search features on Cassandra tables and Cassandra serve as an Elasticsearch data and configuration store. It supports Cassandra vnodes and scales horizontally by adding more nodes.

Elassandra - Elasticsearch + Apache Cassandra

Discover open source projects across all platforms

Projects