DBMS > Apache Druid vs. GBase vs. Ignite vs. Tkrzw vs. ToroDB

System Properties Comparison Apache Druid vs. GBase vs. Ignite vs. Tkrzw vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

An analytical database for business intelligence with large customers in China.

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 concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Document store

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

Score	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	1.04
Rank	#190	Overall
	#88	Relational DBMS

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Score	0.09
Rank	#354	Overall
	#51	Key-value stores

Website

github.com/torodb/server

Technical documentation

druid.apache.org/docs/latest/design

apacheignite.readme.io/docs

Developer

Apache Software Foundation and contributors

Apache Software Foundation

Mikio Hirabayashi

8Kdata

Initial release

2012

2015

2020

2016

Current release

29.0.1, April 2024

GBase 8a

Apache Ignite 2.6

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

AGPL-V3

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++, Java, .Net

C++

Java

Server operating systems

Linux
OS X
Unix

Linux
OS X
Solaris
Windows

Linux
macOS

All OS with a Java 7 VM

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

SQL for querying

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

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

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

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes (replicated cache)

none

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

using specific database classes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Security Hooks for custom implementations

Access rights for users and roles

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