DBMS > Apache Impala vs. jBASE vs. SAP IQ vs. Stardog

System Properties Comparison Apache Impala vs. jBASE vs. SAP IQ vs. Stardog

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A robust multi-value DBMS comprising development tools and middleware

Columnar RDBMS optimized for Big Data analytics

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

column-oriented

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

impala.apache.org

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

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

www.stardog.com

Technical documentation

impala.apache.org/impala-docs.html

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

help.sap.com/docs/SAP_IQ

docs.stardog.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Rocket Software (formerly Zumasys)

SAP, formerly Sybase

Stardog-Union

Initial release

2013

1991

1994

2010

Current release

4.1.0, June 2022

5.7

16.1 SPS04, April 2019

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Server operating systems

Linux

AIX
Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like DML and DDL statements

Embedded SQL for jBASE in BASIC

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
ODBC
RESTful HTTP API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

All languages supporting JDBC/ODBC

.Net
Basic
Jabbascript
Java

C
C#
C++
Java
Perl
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

SAP/Sybase Replication Server

Multi-source replication in HA-Cluster

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

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Access rights for users and roles

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

Cloudera creates observability tool to help enterprises manage cloud costs
6 June 2023, SiliconANGLE News

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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, 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

Temenos signs first customer in India
24 August 2009, Finextra

provided by Google News

New Services in SAP HANA Cloud Lower TCO for Customers in Data-Intensive, Highly Regulated Industries
7 April 2021, SAP News

SAP Again Named a Leader in 2021 Gartner® Magic Quadrant™ for Cloud Database Management Systems
16 December 2021, SAP News

Independent Research Firm Names SAP a Leader in Data Management for Analytics
17 February 2020, SAP News

SAP Scales Out HANA In-Memory For Clouds
6 March 2014, EnterpriseAI

provided by Google News

Share this page