DBMS > atoti vs. GridGain vs. RocksDB vs. SQLite

System Properties Comparison atoti vs. GridGain vs. RocksDB vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

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

Widely used embeddable, in-process RDBMS

Primary database model

Object oriented DBMS

Key-value store
Relational DBMS

Key-value store

Relational DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

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

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

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

docs.atoti.io

www.gridgain.com/docs/index.html

github.com/facebook/rocksdb/wiki

www.sqlite.org/docs.html

Developer

ActiveViam

GridGain Systems, Inc.

Facebook, Inc.

Dwayne Richard Hipp

Initial release

2007

2013

2000

Current release

GridGain 8.5.1

8.11.4, April 2024

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

BSD

Open Source

Public Domain

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

Java, C++, .Net

C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

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

yes

SQL-92 is not fully supported

APIs and other access methods

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

C++ API
Java API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Python

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

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

Durability

Support for making data persistent

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

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