DBMS > Apache Drill vs. Atos Standard Common Repository vs. Ignite vs. Transbase

System Properties Comparison Apache Drill vs. Atos Standard Common Repository vs. Ignite vs. Transbase

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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 resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Key-value store
Relational DBMS

Relational DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

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

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

drill.apache.org

atos.net/en/convergence-creators/portfolio/standard-common-repository

ignite.apache.org

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

Technical documentation

drill.apache.org/docs

apacheignite.readme.io/docs

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

Developer

Apache Software Foundation

Atos Convergence Creators

Apache Software Foundation

Transaction Software GmbH

Initial release

2012

2016

2015

1987

Current release

1.20.3, January 2023

1703

Apache Ignite 2.6

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

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

Java

C++, Java, .Net

C and C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

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

SQL SELECT statement is SQL:2003 compliant

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

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

LDAP

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

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C++

All languages with LDAP bindings

C#
C++
Java
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

user defined functions

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

yes

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

LDAP bind authentication

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Analyse Kafka messages with SQL queries using Apache Drill
23 September 2019, Towards Data Science

Apache Drill case study: A tutorial on processing CSV files
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Using Apache Iceberg for Developing Modern Data Tables
3 October 2023, Open Source For You

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

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Apache Ignite: An Overview
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What is Apache Ignite? How is Apache Ignite Used?
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