DBMS > Dragonfly vs. Ignite vs. jBASE vs. PostGIS vs. Transbase

System Properties Comparison Dragonfly vs. Ignite vs. jBASE vs. PostGIS vs. Transbase

Editorial information provided by DB-Engines

Name

Description

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

A robust multi-value DBMS comprising development tools and middleware

Spatial extension of PostgreSQL

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

Primary database model

Key-value store

Key-value store
Relational DBMS

Multivalue DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

github.com/dragonflydb/dragonfly
www.dragonflydb.io

ignite.apache.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

postgis.net

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

Technical documentation

www.dragonflydb.io/docs

apacheignite.readme.io/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

postgis.net/documentation

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

Developer

DragonflyDB team and community contributors

Apache Software Foundation

Rocket Software (formerly Zumasys)

Transaction Software GmbH

Initial release

2023

2015

1991

2005

1987

Current release

1.0, March 2023

Apache Ignite 2.6

5.7

3.4.2, February 2024

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache 2.0

commercial

Open Source

GPL v2.0

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

C++

C++, Java, .Net

C and C++

Server operating systems

Linux

Linux
OS X
Solaris
Windows

AIX
Linux
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

scheme-free

yes

schema-free

yes

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

yes

optional

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

SQL

Support of SQL

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

Embedded SQL for jBASE in BASIC

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

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

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
Basic
Jabbascript
Java

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

Server-side scripts

Stored procedures

Lua

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

yes

user defined functions

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes (replicated cache)

yes

based on PostgreSQL

Source-replica replication

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

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

Password-based authentication

Security Hooks for custom implementations

Access rights can be defined down to the item level

yes

based on PostgreSQL

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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