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.

Apache Arrow - Powering Columnar In-Memory Analytics 

Graphlite is an embedded graph databases for Python. Graphlite aims to change that by building a simple and fast graph layer over SQLite. Similar to FlockDB, Graphlite only stores adjacency lists, but they can be queried in the style of normal graph databases, e.g. with traversals.

Graphlite - Embedded graph databases for Python

 GridDB is an In-Memory NoSQL Database for highly scalable IoT applications . It has a KVS (Key-Value Store)-type data model that is suitable for sensor data stored in a timeseries. It is a database that can be easily scaled-out according to the number of sensors. High Reliability It is equipped with a structure to spread out the replication of key value data among fellow nodes so that in the event of a node failure, automatic failover can be carried out in a matter of seconds by using the replication function of other nodes.
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GridDB utilizes a “Memory first, Storage second” structure. “Hot” data is kept in-memory, allowing for much faster writes/reads on the most-used data.

 GridDB is an In-Memory NoSQL Database for highly scalable IoT applications . It has a KVS (Key-Value Store)-type data model that is suitable for sensor data stored in a timeseries. It is a database that can be easily scaled-out according to the number of sensors. High Reliability It is equipped with a structure to spread out the replication of key value data among fellow nodes so that in the event of a node failure, automatic failover can be carried out in a matter of seconds by using the replication function of other nodes. 

Griddb - High performance, High scalability and High reliability database for big data

Jimfs is an in-memory implementation of Java 7's java.nio.file abstract file system API. imfs supports almost all the APIs under java.nio.file. Jimfs also supports creating file systems that, for example, use Windows-style paths and (to an extent) behavior. In general, however, file system behavior is modeled after UNIX and may not exactly match any particular real file system or platform.
  

jimfs - An in-memory file system for Java 7+

A high performance in-memory key-value item storage engine written in golang. The storage engine is based lock-free data structures and scales well with multicore CPUs.

nitro - A high performance in-memory index storage engine

Cache library for golang. It supports expirable Cache, LFU, LRU and ARC.Supports expirable Cache, LFU, LRU and ARC.

gcache - Cache library for golang. It supports expirable Cache, LFU, LRU and ARC.

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Apache Arrow - Powering Columnar In-Memory Analytics

Graphlite - Embedded graph databases for Python

Griddb - High performance, High scalability and High reliability database for big data

jimfs - An in-memory file system for Java 7+

nitro - A high performance in-memory index storage engine

gcache - Cache library for golang. It supports expirable Cache, LFU, LRU and ARC.

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Apache Arrow - Powering Columnar In-Memory Analytics

Graphlite - Embedded graph databases for Python

Griddb - High performance, High scalability and High reliability database for big data

jimfs - An in-memory file system for Java 7+

nitro - A high performance in-memory index storage engine

gcache - Cache library for golang. It supports expirable Cache, LFU, LRU and ARC.

TechStack

Tagcloud

License