DBMS > GridGain vs. HEAVY.AI vs. LokiJS vs. Postgres-XL

System Properties Comparison GridGain vs. HEAVY.AI vs. LokiJS vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

In-memory JavaScript DBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

www.gridgain.com

github.com/heavyai/heavydb
www.heavy.ai

github.com/techfort/LokiJS

www.postgres-xl.org

Technical documentation

www.gridgain.com/docs/index.html

docs.heavy.ai

techfort.github.io/LokiJS

www.postgres-xl.org/documentation

Developer

GridGain Systems, Inc.

HEAVY.AI, Inc.

Initial release

2007

2016

2014

since 2012, originally named StormDB

Current release

GridGain 8.5.1

5.10, January 2022

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

Mozilla public license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, C++, .Net

C++ and CUDA

JavaScript

Server operating systems

Linux
OS X
Solaris
Windows

Linux

server-less, requires a JavaScript environment (browser, Node.js)

Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

XML type, but no XML query functionality

Secondary indexes

yes

via views

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

distributed, parallel query execution

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
ODBC
Thrift
Vega

JavaScript API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

View functions in JavaScript

user defined functions

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

atomic operations within a single collection possible

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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