DBMS > Ignite vs. InterSystems Caché vs. Transbase vs. XTDB

System Properties Comparison Ignite vs. InterSystems Caché vs. Transbase vs. XTDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

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 multi-model DBMS and application server

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store
Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Document store

Secondary database models

Document store

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

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

ignite.apache.org

www.intersystems.com/products/cache

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

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

apacheignite.readme.io/docs

docs.intersystems.com

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

www.xtdb.com/docs

Developer

Apache Software Foundation

InterSystems

Transaction Software GmbH

Juxt Ltd.

Initial release

2015

1997

1987

2019

Current release

Apache Ignite 2.6

2018.1.4, May 2020

Transbase 8.3, 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free development license

Open Source

MIT 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++, Java, .Net

C and C++

Clojure

Server operating systems

Linux
OS X
Solaris
Windows

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

depending on used data model

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

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

.NET Client API
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST
JDBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C#
C++
Java

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

Clojure
Java

Server-side scripts

Stored procedures

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

yes

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Source-replica replication

yes, each node contains all data

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

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

GridGain Showcases Power of Apache Ignite at Community Over Code Conference
5 October 2023, Datanami

Apache Ignite: An Overview
6 September 2023, Open Source For You

GridGain Unified Real-Time Data Platform Version 8.9 Addresses Today's More Complex Real-Time Data Processing ...
12 October 2023, GlobeNewswire

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

provided by Google News

AWS, GCP, Oracle, Azure, SAP Lead Cloud DBMS Market: Gartner
12 February 2022, CRN

Epic On EHR Interoperability: Not A '1-Time Project'
10 April 2015, InformationWeek

Associative Data Modeling Demystified - Part1 - DataScienceCentral.com
9 July 2016, Data Science Central

Announcing IBM Spectrum Sentinel: Building a Cyber Resilient Future
24 June 2022, IBM

Choosing a Database Technology. A roadmap and process overview | by Shirish Joshi
23 February 2020, Towards Data Science

provided by Google News

Share this page