Search Results for "build-updates"
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Showing 10 open source projects for "build-updates"
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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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Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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ReadySet
Readyset is a MySQL and Postgres wire-compatible caching layer
ReadySet is a SQL caching engine designed to improve query response times and scalability for PostgreSQL and MySQL databases. It acts as a transparent caching layer, automatically maintaining cached query results and serving them with sub-millisecond latency, without requiring changes to application code. -
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Meilisearch
An open-source, lightning-fast, and hyper-relevant search engine
An open-source, lightning-fast, and hyper-relevant search engine that fits effortlessly into your apps, websites, and workflow. Meilisearch is a flexible and powerful user-focused search engine that can be added to any website or application. Search-as-you-type returns answers in less than 50 milliseconds. That's faster than the blink of an eye! Deploy in a matter of minutes. Smart presets let you start searching through your data with zero configuration. Send data to Meilisearch however you... -
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RisingWave
RisingWave: the next-generation streaming database in the cloud
RisingWave is a cloud-native streaming database that uses SQL as the interface. It is designed to reduce the complexity and cost of building real-time applications. RisingWave consumes streaming data, performs continuous queries, and updates results dynamically. As a database system, RisingWave maintains results in its own storage so that users can access data efficiently. RisingWave accepts data from sources like Apache Kafka, Apache Pulsar, Amazon Kinesis, Redpanda, and materialized CDC sources. Everything you do in RisingWave is via Postgres-compatible SQL. Create materialized views for the data that need to be incrementally aggregated. ... -
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Neon Database
Neon: Serverless Postgres. We separated storage and compute
The database you love, on a serverless platform designed to help you build reliable and scalable applications faster. Focus on building applications with time and money-saving features like instant provisioning, autoscaling according to load, and scale to zero. Instantly branch your data and schema to access isolated DB copies for development, CI/CD, and schema migrations with copy-on-write storage. Integrate it into your language or framework within minutes and unlock a simpler developer workflow. -
Go From Idea to Deployed AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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Lantern Database
PostgreSQL vector database extension for building AI applications
Lantern is a real-time data transformation engine that enables data engineers to build, run, and monitor streaming data pipelines with SQL. It’s designed to process events in motion, offering low-latency stream transformations, aggregations, and enrichment in a declarative way. Lantern is especially suited for modern data infrastructure and analytics platforms. -
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SQLpage
Fast SQL-only data application builder
SQLPage is a rapid application development tool that enables developers to build data-driven web applications using only SQL queries. By writing simple .sql files, users can create interactive web pages that display data as text, lists, grids, plots, and forms, streamlining the process of developing data applications without extensive frontend coding. -
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Trailbase
A blazingly fast, open-source application server with type-safe APIs
A blazingly fast, open-source application server with type-safe APIs, built-in JS/ES6/TS Runtime, Auth, and Admin UI built on Rust, SQLite & V8. Simplify with fewer moving parts: an easy-to-self-host, single-file, extensible backend for your mobile, web, or desktop application. Sub-millisecond latencies eliminate the need for dedicated caches, no more stale or inconsistent data. -
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rust-rocksdb
Rust wrapper for rocksdb
Binding is statically linked with a specific version of RocksDB. If you want to build it yourself, make sure you've also cloned the RocksDB and compression submodules. By default, support for the Snappy, LZ4, Zstd, Zlib, and Bzip2 compression is enabled through crate features. If support for all of these compression algorithms is not needed, default features can be disabled and specific compression algorithms can be enabled. -
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MongoDB Rust Driver
The official MongoDB Rust Driver
...The driver supports common MongoDB features like CRUD operations, indexing, aggregations, change streams, and transactions, enabling full use of the database’s capabilities from Rust applications. Because it’s asynchronous by design, it works well with Rust async runtimes like Tokio and async-std, letting developers build highly concurrent networked services that efficiently use modern multicore hardware. The crate also includes BSON encoding and decoding that maps cleanly to Rust types, so developers can work with rich document structures while retaining Rust’s performance guarantees. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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10
sled
The champagne of beta embedded databases
...Forward and reverse iterators over ranges of items. A crash-safe monotonic ID generator capable of generating 75-125 million unique ID's per second. Zstd compression (use the compression build feature, disabled by default). Cpu-scalable lock-free implementation. Flash-optimized log-structured storage. Uses modern b-tree techniques such as prefix encoding and suffix truncation for reducing the storage costs of long keys with shared prefixes. If keys are the same length and sequential then the system can avoid storing 99%+ of the key data in most cases, essentially acting like a learned index. sled performs prefix encoding on long keys with similar prefixes that are grouped together in a range, as well as suffix truncation to further reduce the indexing costs of long keys.
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