DBMS > Apache Impala vs. Ingres vs. OpenQM vs. SWC-DB vs. Transbase

System Properties Comparison Apache Impala vs. Ingres vs. OpenQM vs. SWC-DB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Well established RDBMS

QpenQM is a high-performance, self-tuning, multi-value DBMS

A high performance, scalable Wide Column DBMS

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

Primary database model

Secondary database models

Document store

Time Series DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

impala.apache.org

www.actian.com/databases/ingres

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

github.com/kashirin-alex/swc-db
www.swcdb.org

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

Technical documentation

impala.apache.org/impala-docs.html

docs.actian.com/ingres

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

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Actian Corporation

Rocket Software, originally Martin Phillips

Alex Kashirin

Transaction Software GmbH

Initial release

2013

1974

originally developed at University Berkely in early 1970s

1993

2020

1987

Current release

4.1.0, June 2022

11.2, May 2022

3.4-12

0.5, April 2021

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

GPLv2, extended commercial license available

Open Source

GPL V3

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 and C++

Server operating systems

Linux

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

with some exceptions

schema-free

yes

Typing

predefined data types such as float or date

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Proprietary protocol
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
Basic
C
Java
Objective C
PHP
Python

C++

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Ingres Replicator

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

StarRocks Brings Speedy OLAP Database to the Cloud
14 July 2022, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

Postgres pioneer Michael Stonebraker promises to upend the database once more
26 December 2023, The Register

New startup from Postgres creator puts the database at heart of software stack
12 March 2024, TechCrunch

Actian Launches Ingres as a Fully-Managed Cloud Service
24 September 2021, Integration Developers

PostgreSQL now top developer choice ahead of MySQL, according to massive new survey • DEVCLASS
13 June 2023, DevClass

Dr. Michael Stonebraker: A Short History of Database Systems
1 February 2019, The New Stack

provided by Google News

2022 All O-Zone Football Team
17 December 2022, Ozarks Sports Zone

provided by Google News

Share this page