Displaying 1 to 15 from 15 results

Trino - A query engine that runs at ludicrous speed

  •    Java

Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low latency analytics. It is an ANSI SQL compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset and many others. It helps to natively query data in Hadoop, S3, Cassandra, MySQL, and many others, without the need for complex, slow, and error-prone processes for copying the data.

Presto - Distributed SQL query engine for big data

  •    Java

Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes. It allows querying data from relational / nosql databases. A single Presto query can combine data from multiple sources, allowing for analytics across your entire organization. It is developed by Facebook.

Kylin - Extreme OLAP Engine for Big Data

  •    Java

Apache Kylin is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop supporting extremely large datasets, original contributed from eBay Inc. It is designed to reduce query latency on Hadoop for 10+ billions of rows of data. It offers ANSI SQL on Hadoop and supports most ANSI SQL query functions.

storm - Simple and powerful toolkit for BoltDB

  •    Go

Storm is a simple and powerful toolkit for BoltDB. Basically, Storm provides indexes, a wide range of methods to store and fetch data, an advanced query system, and much more.In addition to the examples below, see also the examples in the GoDoc.




Apache Arrow - Powering Columnar In-Memory Analytics

  •    Java

Apache arrow is an open source, low latency SQL query engine for Hadoop and NoSQL. Arrow enables execution engines to take advantage of the latest SIMD (Single input multiple data) operations included in modern processors, for native vectorized optimization of analytical data processing. Columnar layout of data also allows for a better use of CPU caches by placing all data relevant to a column operation in as compact of a format as possible.

atomspace - The OpenCog hypergraph database, query system and rule engine

  •    C++

The OpenCog AtomSpace is a knowledge representation (KR) database and the associated query/reasoning engine to fetch and manipulate that data, and perform reasoning on it. Data is represented in the form of graphs, and more generally, as hypergraphs; thus the AtomSpace is a kind of graph database, the query engine is a general graph re-writing system, and the rule-engine is a generalized rule-driven inferencing system. The vertices and edges of a graph, known as "Atoms", are used to represent not only "data", but also "procedures"; thus, many graphs are executable programs as well as data structures. The AtomSpace is a platform for building Artificial General Intelligence (AGI) systems. It provides the central knowledge representation component for OpenCog. As such, it is a fairly mature component, on which a lot of other systems are built, and which depend on it for stable, correct operation in a day-to-day production environment.

qlbridge - A golang SQL expression VM. Library to build query engine based functionality.

  •    Go

A SQL execution engine for embedded use as a library for Sql OR sql-Like functionality. Hackable, add datasources, functions. See usage in https://github.com/dataux/dataux a federated Sql Engine mysql-compatible with backends (Elasticsearch, Google-Datastore, Mongo, Cassandra, Files).See example in qlcsv folder for a CSV reader, parser, evaluation engine.

bullet-storm - The Apache Storm implementation of the Bullet backend

  •    Java

This project implements Bullet on Storm. It also includes the PubSub implementation that uses Storm DRPC as the PubSub.All documentation has moved to Github Pages here.


qcache - In memory cache server with query capabilities

  •    Python

QCache is a key-table cache, an in memory cache server with analytical query capabilities. While the more commonly known key-value caches (such as Memcached) lets you fetch a value based on a key QCache lets you run queries against a table based on a key.

jsonquery-engine - A full MongoDB query language implementation with INDEXES for querying your levelup/leveldb database

  •    Javascript

A full MongoDB query language implementation with INDEXES for querying your levelup/leveldb database. This is a plugin for level-queryengine.

subindex - Generic pluggable indexing system for leveldb/levelup

  •    Javascript

Generic pluggable indexing system for leveldb/levelup. Designed to be used with level-queryengine to create efficient searches on levelup with pluggable query languages/systems, that require specialized indexing strategies.

dataux - Federated mysql compatible proxy to elasticsearch, mongo, cassandra, big-table, google datastore

  •    Go

Unify disparate data sources and files into a single Federated view of your data and query with SQL without copying into datawarehouse. Mysql compatible federated query engine to Elasticsearch, Mongo, Google Datastore, Cassandra, Google BigTable, Kubernetes, file-based sources. This query engine hosts a mysql protocol listener, which rewrites sql queries to native (elasticsearch, mongo, cassandra, kuberntes-rest-api, bigtable). It works by implementing a full relational algebra distributed execution engine to run sql queries and poly-fill missing features from underlying sources. So, a backend key-value storage such as cassandra can now have complete WHERE clause support as well as aggregate functions etc.

sparql-engine - 🚂 A framework for building SPARQL query engines in Javascript/Typescript

  •    TypeScript

An open-source framework for building SPARQL query engines in Javascript/Typescript. The sparql-engine framework allow you to build a custom SPARQL query engine on top of any data storage system.

QLever - Very fast SPARQL Engine, which can handle very large datasets like Wikidata, offers context-sensitive Autocompletion for SPARQL queries, and allows combination with Text Search

  •    C++

QLever (pronounced "Clever") is an efficient SPARQL engine, which can handle very large dataset with tens of billions of triples on a standard PC or server. For example, QLever can index the complete Wikidata (18 billion triples) in less than 24 hours and execute typical queries in less than a second, using no more than 40 GB of RAM. QLever is also fast for queries that produce large or very large results (millions of rows per second). Other SPARQL engines, like Virtuoso or Blazegraph, are very slow, when large sequences of IRIs or literals have to be materialized. On top of the standard SPARQL functionality, QLever also supports search in TEXT associated with the knowledge base as well as SPARQL Autocompletion. These are described on the advanced features page.

qcert - Compilation and Verification of Data-Centric Languages

  •    Coq

This is the source code for Q*cert, a framework for the development and verification of domain specific languages. It supports a rich data model and includes an extensive compilation pipeline 'out of the box'. Applications include query languages (e.g., SQL, OQL), rules languages (e.g., JRules) and smart contract languages (e.g., Ergo). Q*cert is built with the Coq proof assistant (https://coq.inria.fr). A significant subset of the provided compilation pipeline has been mechanically checked for correctness.






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