DBMS > GigaSpaces vs. Tarantool

System Properties Comparison GigaSpaces vs. Tarantool

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Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Secondary database models

Graph DBMS
Search engine

Document store
Relational DBMS
Spatial DBMS

with Tarantool/GIS extension

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

Score	1.52
Rank	#171	Overall
	#29	Document stores
	#8	Object oriented DBMS

Score	1.81
Rank	#152	Overall
	#27	Key-value stores

Website

www.gigaspaces.com

www.tarantool.io

Technical documentation

docs.gigaspaces.com/latest/landing.html

www.tarantool.io/en/doc

Developer

Gigaspaces Technologies

Initial release

2000

2008

Current release

15.5, September 2020

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

BSD

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 C++

Server operating systems

Linux
macOS
Solaris
Windows

BSD
Linux
macOS

Data scheme

schema-free

schema-free, schema definition possible

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

Full-featured ANSI SQL support

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

Open binary protocol

Supported programming languages

.Net
C++
Java
Python
Scala

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

Lua, C and SQL stored procedures

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Hash sharding based on virtual buckets

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

yes, with SQL

Transaction concepts

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

ACID

ACID, read commited

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, regular snapshots on disk, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Role-based access control

Access rights for users and roles

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More resources

DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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Recent citations in the news

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