DBMS > GridGain vs. JaguarDB vs. LevelDB vs. Sequoiadb vs. YottaDB

System Properties Comparison GridGain vs. JaguarDB vs. LevelDB vs. Sequoiadb vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

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

Performant, highly scalable DBMS for AI and IoT applications

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

NewSQL database with distributed OLTP and SQL

A fast and solid embedded Key-value store

Primary database model

Key-value store
Relational DBMS

Key-value store
Vector DBMS

Key-value store

Document store
Relational DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

www.gridgain.com

www.jaguardb.com

github.com/google/leveldb

www.sequoiadb.com

yottadb.com

Technical documentation

www.gridgain.com/docs/index.html

www.jaguardb.com/support.html

github.com/google/leveldb/blob/main/doc/index.md

www.sequoiadb.com/en/index.php?m=Files&a=index

yottadb.com/resources/documentation

Developer

GridGain Systems, Inc.

DataJaguar, Inc.

Google

Sequoiadb Ltd.

YottaDB, LLC

Initial release

2007

2015

2011

2013

2001

Current release

GridGain 8.5.1

3.3 July 2023

1.23, February 2021

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

BSD

Open Source

Server: AGPL; Client: Apache V2

Open Source

AGPL 3.0

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++

the server part. Clients available in other languages

C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux

Illumos
Linux
OS X
Windows

Linux

Docker
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

by using the Octo plugin

APIs and other access methods

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

JDBC
ODBC

proprietary protocol using JSON

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C++
Java
PHP
Python

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

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

JavaScript

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Multi-source replication

none

Source-replica replication

yes

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

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Document is locked during a transaction

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

rights management via user accounts

simple password-based access control

Users and groups based on OS-security mechanisms

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