DBMS > Apache Impala vs. Atos Standard Common Repository vs. HyperSQL vs. Postgres-XL vs. Tkrzw

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. HyperSQL vs. Postgres-XL vs. Tkrzw

Editorial information provided by DB-Engines

Name

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

Description

Analytic DBMS for Hadoop

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Key-value store

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

impala.apache.org

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

hsqldb.org

www.postgres-xl.org

dbmx.net/tkrzw

Technical documentation

impala.apache.org/impala-docs.html

hsqldb.org/web/hsqlDocsFrame.html

www.postgres-xl.org/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Atos Convergence Creators

Mikio Hirabayashi

Initial release

2013

2016

2001

2014

since 2012, originally named StormDB

2020

Current release

4.1.0, June 2022

1703

2.7.2, June 2023

10 R1, October 2018

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

based on BSD license

Open Source

Mozilla public license

Open Source

Apache Version 2.0

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

C++

Server operating systems

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
macOS

Data scheme

yes

Schema and schema-less with LDAP views

yes

schema-free

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC

LDAP

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

All languages supporting JDBC/ODBC
Java

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java, SQL

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

none

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 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

MVCC

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

LDAP bind authentication

fine grained access rights according to SQL-standard

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More resources

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