DBMS > Altibase vs. Apache Impala vs. Apache Kylin vs. PostgreSQL vs. Riak TS

System Properties Comparison Altibase vs. Apache Impala vs. Apache Kylin vs. PostgreSQL vs. Riak TS

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Analytic DBMS for Hadoop

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Time Series DBMS

Secondary database models

Document store

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

impala.apache.org/impala-docs.html

kylin.apache.org/docs

www.postgresql.org/docs

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Altibase

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation, originally contributed from eBay Inc

PostgreSQL Global Development Group

www.postgresql.org/developer

Open Source, formerly Basho Technologies

Initial release

1999

2013

2015

1989

1989: Postgres, 1996: PostgreSQL

2015

Current release

v7.3, 2023, August 2023

4.1.0, June 2022

3.1.0, July 2020

16.3, May 2024

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

Erlang

Server operating systems

AIX
HP-UX
Linux

Linux

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux
OS X

Data scheme

yes

schema-free

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

restricted

SQL

Support of SQL

ANSI SQL-92

SQL-like DML and DDL statements

ANSI SQL for queries (using Apache Calcite)

yes

standard with numerous extensions

yes, limited

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

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

HTTP API
Native Erlang Interface

Supported programming languages

C
C++
Java

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

user defined functions and integration of map-reduce

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Source-replica replication

other methods possible by using 3rd party extensions

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

More information provided by the system vendor

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