DBMS > Datomic vs. GridGain vs. LokiJS vs. RocksDB

System Properties Comparison Datomic vs. GridGain vs. LokiJS vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

In-memory JavaScript DBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store

Key-value store

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

www.datomic.com

www.gridgain.com

github.com/techfort/LokiJS

rocksdb.org

Technical documentation

docs.datomic.com

www.gridgain.com/docs/index.html

techfort.github.io/LokiJS

github.com/facebook/rocksdb/wiki

Developer

Cognitect

GridGain Systems, Inc.

Facebook, Inc.

Initial release

2012

2007

2014

2013

Current release

1.0.6735, June 2023

GridGain 8.5.1

8.11.4, April 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

Java, C++, .Net

JavaScript

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

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

Linux

Data scheme

yes

schema-free

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

Secondary indexes

yes

via views

SQL

Support of SQL

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

APIs and other access methods

RESTful HTTP API

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

JavaScript API

C++ API
Java API

Supported programming languages

Clojure
Java

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

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

View functions in JavaScript

Triggers

By using transaction functions

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes (replicated cache)

none

yes

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

Foreign keys

Referential integrity

Transaction concepts

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

ACID

atomic operations within a single collection possible

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

yes

User concepts

Access control

Security Hooks for custom implementations

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