DBMS > Apache Impala vs. Datomic vs. Kingbase vs. SAP HANA vs. SAP IQ

System Properties Comparison Apache Impala vs. Datomic vs. Kingbase vs. SAP HANA vs. SAP IQ

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

In-memory, column based data store. Available as appliance or cloud service

Columnar RDBMS optimized for Big Data analytics

Primary database model

Relational DBMS

column-oriented

Secondary database models

Document store

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Website

impala.apache.org

www.datomic.com

www.kingbase.com.cn

www.sap.com/products/hana.html

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

impala.apache.org/impala-docs.html

docs.datomic.com

help.sap.com/hana

help.sap.com/docs/SAP_IQ

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Cognitect

BeiJing KINGBASE Information technologies inc.

SAP

SAP, formerly Sybase

Initial release

2013

2012

1999

2010

1994

Current release

4.1.0, June 2022

1.0.7075, December 2023

V8.0, August 2021

2.0 SPS07 (April 4, 2023), April 2023

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

limited edition free

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java, Clojure

C and Java

Server operating systems

Linux

All OS with a Java VM

Linux
Windows

Appliance or cloud-service

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Standard with numerous extensions

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

JDBC
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Transaction Functions

user defined functions

SQLScript, R

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

horizontal partitioning (by range, list and hash) and vertical partitioning

yes

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

But extensive use of caching in the application peers

yes

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Hadoop integration

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

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

yes

fine grained access rights according to SQL-standard

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