Search Results for "throughput"
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Showing 37 open source projects for "throughput"
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1
Garnet
Garnet is a remote cache-store from Microsoft Research
Garnet is a remote cache‑store developed by Microsoft Research. It delivers high throughput and low‑latency performance, supports scalability via clustering (sharding, replication, key migration, checkpointing, failover, transactions), and seamlessly integrates with existing Redis clients. Garnet offers much better throughput and scalability with many client connections and small batches, relative to comparable open-source cache-stores, leading to cost savings for large apps and services. ... -
2
Canal
MySQL binlog
Canal is an open-source project developed by Alibaba that simulates MySQL slave functionality to parse MySQL binlog files. It enables real-time data synchronization and change data capture (CDC) between MySQL and other systems such as Elasticsearch, Kafka, or HBase. Canal is widely used for data integration, replication, and monitoring across distributed systems, offering high performance and low-latency log parsing. -
3
Motor
The async Python driver for MongoDB and Tornado or asyncio
...It provides a familiar API surface similar to the official synchronous PyMongo driver, so you can migrate or write MongoDB code in Python without having to learn a completely new interface. Because it integrates with popular async ecosystems like FastAPI, Sanic, and aiohttp, Motor is a natural fit for modern async Python stacks where throughput and responsiveness matter. It also supports change streams, grid file system (GridFS), and the full range of CRUD and aggregation operations available in MongoDB. -
4
ConcourseDB
Distributed database warehouse for transactions, search and analytics
ConcourseDB is a distributed, self-tuning database designed for real-time applications, offering strong consistency and ACID compliance without requiring complex configurations. It provides dynamic schema support and automatic indexing. -
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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Reliable PostgreSQL Backup & Restore
Reliable PostgreSQL backup and restore
...Compression is usually the bottleneck during backup operations but, even with now-ubiquitous multi-core servers, most database backup solutions are still single-process. pgBackRest solves the compression bottleneck with parallel processing. Utilizing multiple cores for compression makes it possible to achieve 1TB/hr raw throughput even on a 1Gb/s link. More cores and a larger pipe lead to even higher throughput. A custom protocol allows pgBackRest to backup, restore, and archive locally or remotely via TLS/SSH with minimal configuration. An interface to query PostgreSQL is also provided via the protocol layer so that remote access to PostgreSQL is never required, which enhances security. -
6
Olric
Distributed, in-memory key/value store and cache
A lightweight, distributed in-memory data store designed for key-value caching and ephemeral storage. -
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PikiwiDB
Pika is a Redis-Compatible database
A high-performance, distributed key-value database inspired by Redis but designed for large-scale cloud-native environments. -
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r2dbc-postgresql
Postgresql R2DBC Driver
r2dbc-postgresql is a reactive PostgreSQL driver for the JVM based on the R2DBC (Reactive Relational Database Connectivity) specification. It allows non-blocking, asynchronous access to PostgreSQL databases, making it ideal for reactive Java or Kotlin applications built with frameworks like Spring WebFlux. -
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PolarDB for PostgreSQL
A cloud-native database based on PostgreSQL developed by Alibaba Cloud
PolarDB for PostgreSQL is Alibaba Cloud's cloud-native, distributed version of PostgreSQL designed for high availability, scalability, and performance. It enhances standard PostgreSQL with features like shared storage, compute-storage separation, and parallel processing. PolarDB supports cloud-native workloads, offering enterprise-grade capabilities while maintaining PostgreSQL compatibility. -
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10
OrioleDB
Building a modern cloud-native storage engine
...Designed as a table access method (TAM) extension, it introduces features like MVCC improvements, compression, and efficient concurrency handling. OrioleDB seeks to future-proof PostgreSQL by enabling cloud-native, high-throughput workloads without altering the core PostgreSQL behavior. -
11
Cortex
A horizontally scalable, multi-tenant, long term Prometheus
...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. -
12
SPQR
Stateless Postgres Query Router
SPQR is a sharding proxy for PostgreSQL that enables horizontal scalability by distributing queries across multiple PostgreSQL instances. Designed for large-scale, multi-tenant architectures, SPQR routes, rewrites, and manages SQL queries to ensure they are executed efficiently across shards. It provides a PostgreSQL-compatible interface so applications can scale transparently without code changes. -
13
QuestDB
An open source SQL database designed to process time series data
QuestDB is a high-performance, open-source SQL database for applications in financial services, IoT, machine learning, DevOps and observability. 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. ... -
14
Dragonfly
A modern replacement for Redis and Memcached
...Designed to fully utilize the power of modern cloud hardware and deliver on the data demands of modern applications, Dragonfly frees developers from the limits of traditional in-memory data stores. The power of modern cloud hardware can never be realized with legacy software. Dragonfly is optimized for modern cloud computing, delivering 25x more throughput and 12x lower snapshotting latency when compared to legacy in-memory data stores like Redis, making it easy to deliver the real-time experience your customers expect. Scaling Redis workloads is expensive due to their inefficient, single-threaded model. Dragonfly is far more compute and memory efficient, resulting in up to 80% lower infrastructure costs. ... -
15
Zvec
A lightweight, lightning-fast, in-process vector database
...Developed by Alibaba’s Tongyi Lab, it positions itself as the “SQLite of vector databases” by being easy to integrate, minimal in dependencies, and capable of handling high throughput with low latency on edge devices or small systems. Zvec excels at approximate nearest neighbor search and retrieval tasks that power features like semantic search, recommendation systems, and retrieval-augmented generation (RAG) setups. Its performance benchmarks show it achieving high queries-per-second and fast index build times compared to similar tools. ... -
16
ZeusDB Vector Database
Blazing-fast vector DB with similarity search and metadata filtering
ZeusDB is a vector database built for fast, scalable similarity search with strong production ergonomics. It combines high-performance approximate nearest neighbor indexes with clean APIs and metadata filtering so applications can retrieve semantically relevant items at low latency. The storage layer is designed for durability and growth, supporting sharding, replication, and background compaction while keeping query tails predictable. Developers get multiple ingestion paths—batch,... -
17
Nebula Graph
A distributed, fast open-source graph database
The graph database built for super large-scale graphs with milliseconds of latency. Optimized SUBGRAPH and FIND PATH for better performance. Optimized query paths to reduce redundant paths and time complexity. Optimized the method to get properties for better performance of MATCH statements. Nebula Graph adopts the Apache 2.0 license, one of the most permissive free software licenses in the world. Free as in freedom, because, under the Apache 2.0 license, you can use, copy, modify and... -
18
Greenplum Database
Massive parallel data platform for analytics, machine learning and AI
...With its unique cost-based query optimizer designed for large-scale data workloads, Greenplum scales interactive and batch-mode analytics to large datasets in the petabytes without degrading query performance and throughput. Based on PostgreSQL, Greenplum provides you with more control over the software you deploy, reducing vendor lock-in, and allowing open influence on product direction. Greenplum reduces data silos by providing you with a single, scale-out environment for converging analytic and operational workloads, like streaming ingestion. All major Greenplum contributions are part of the Greenplum Database project and share the same database core, including the MPP architecture, analytical interfaces, and security capabilities. -
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GT.M High end TP database engine
Industrial Strength NoSQL Application Development Platform
GT.M[tm] is a vetted industrial strength, transaction processing application platform consisting of a key-value database engine optimized for extreme transaction processing throughput & business continuity. -
20
Skiplist-CPP
A tiny KV storage based on skiplist written in C++ language
...Beyond in-memory operations, it demonstrates persistence through data dump to disk and reload, turning the structure into a tiny embeddable database. Stress-test scripts and example binaries are provided so you can benchmark throughput and validate correctness on your own machine. This makes the repo valuable for learners studying database internals and for practitioners who want a starting point for an embedded KV engine or educational experiments. -
21
DBD2
A multi-threaded, multi-database tcp-based database insertion app.
DBD2 inserts database records from TCP input. It is a companion project to Syslgod2 and an application in its own right. It ships with a backgrounding client for generic use. The client sends whatever information the user puts on the command-line to the back-end daemon via TCP. Upon successful transmission, the client exits. On failure, it backs off and retries until its life-time timer expires. The back-end daemon accepts data from Syslogd2 or its own client and inserts that data... -
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Apache Pegasus
A consistent and high-performance key-value store
A distributed key-value store optimized for low-latency and high-throughput applications, developed by Apache Incubator. -
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RethinkDB
The open-source database for the realtime web
...RethinkDB can be used for a number of different things: building realtime trading and optimization engines; simplifying the data infrastructure in multiplayer games to produce low latency, high throughput realtime interactions; building reactive web and mobile apps with a lot less effort, and so much more. -
24
KeyDB
A Multithreaded Fork of Redis
KeyDB is an incredibly fast NoSQL database, a high performance fork of Redis that can perform up to 5X faster than Redis and can be used as a drop in alternative. KeyDB is focused on multithreading, memory efficiency, and high throughput, with features and capabilities not readily available with Redis. KeyDB has gained quite a reputation for its exceptional performance and features. Apart from multithreading it offers such features as multi-master replication, persistence capabilities, horizontal and vertical scalability and direct backup to AWS S3 right out of the box. ... -
25
SnappyData
Memory optimized analytics database, based on Apache Spark
SnappyData (aka TIBCO ComputeDB) is a distributed, in-memory optimized analytics database. SnappyData delivers high throughput, low latency, and high concurrency for a unified analytics workload. By fusing an in-memory hybrid database inside Apache Spark, it provides analytic query processing, mutability/transactions, access to virtually all big data sources and stream processing all in one unified cluster. One common use case for SnappyData is to provide analytics at interactive speeds over large volumes of data with minimal or no pre-processing of the dataset. ...
