DBMS > Hazelcast vs. PostGIS vs. Tarantool vs. Transbase

System Properties Comparison Hazelcast vs. PostGIS vs. Tarantool vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

Spatial extension of PostgreSQL

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Key-value store

Spatial DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Relational DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

hazelcast.com

postgis.net

www.tarantool.io

www.transaction.de/en/products/transbase.html

Technical documentation

hazelcast.org/imdg/docs

postgis.net/documentation

www.tarantool.io/en/doc

www.transaction.de/en/products/transbase/features.html

Developer

Hazelcast

Transaction Software GmbH

Initial release

2008

2005

2008

1987

Current release

5.3.6, November 2023

3.4.2, February 2024

2.10.0, May 2022

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL v2.0

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

commercial

free development 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 and C++

Server operating systems

All OS with a Java VM

BSD
Linux
macOS

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

yes

Typing

predefined data types such as float or date

yes

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

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

Full-featured ANSI SQL support

yes

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

Open binary protocol

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

user defined functions

Lua, C and SQL stored procedures

yes

Triggers

yes

Events

yes

yes, before/after data modification events, on replication events, client session events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

yes

based on PostgreSQL

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

yes, write ahead logging

yes

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

yes

based on PostgreSQL

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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

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