Displaying 1 to 6 from 6 results

datascript - Immutable database and Datalog query engine for Clojure, ClojureScript and JS

  •    Clojure

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.

snappydata - SnappyData - The Spark Database. Stream, Transact, Analyze, Predict in one cluster

  •    Scala

Apache Spark is a general purpose parallel computational engine for analytics at scale. At its core, it has a batch design center and is capable of working with disparate data sources. While this provides rich unified access to data, this can also be quite inefficient and expensive. Analytic processing requires massive data sets to be repeatedly copied and data to be reformatted to suit Spark. In many cases, it ultimately fails to deliver the promise of interactive analytic performance. For instance, each time an aggregation is run on a large Cassandra table, it necessitates streaming the entire table into Spark to do the aggregation. Caching within Spark is immutable and results in stale insight. At SnappyData, we take a very different approach. SnappyData fuses a low latency, highly available in-memory transactional database (GemFireXD) into Spark with shared memory management and optimizations. Data in the highly available in-memory store is laid out using the same columnar format as Spark (Tungsten). All query engine operators are significantly more optimized through better vectorization and code generation. The net effect is, an order of magnitude performance improvement when compared to native Spark caching, and more than two orders of magnitude better Spark performance when working with external data sources.

snappydata - Project SnappyData - memory optimized analytics database, based on Apache Spark™ and Apache Geode™

  •    Scala

SnappyData (aka TIBCO ComputeDB) is a distributed, in-memory optimized analytics database. SnappyData delivers high throughput, low latency, and high concurrency for 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. For instance, there is no need to often pre-aggregate/reduce or generate cubes over your large data sets for ad-hoc visual analytics. This is made possible by smartly managing data in-memory, dynamically generating code using vectorization optimizations and maximizing the potential of modern multi-core CPUs. SnappyData enables complex processing on large data sets in sub-second timeframes.

WhiteDB - NoSQL Memory Database in C

  •    C

WhiteDB is a lightweight NoSQL database library written in C, operating fully in main memory. There is no server process. Data is read and written directly from/to shared memory, no sockets are used between WhiteDB and the application program. It supports indexes (T-tree), concurrency through locking, persistence through logging and memory dumps, json, CSV and RDF support, easy to use in embedded systems and lot more.




aranGoDriver - ArangoDB-driver in golang

  •    Go

This project is a golang-driver for ArangoDB writen in go. There is also an embedded-in-memory-Database to run all your tests. All you need is a running Arango-DB and a go-environment.