DBMS > Apache Impala vs. ArcadeDB vs. SAP IQ vs. STSdb

System Properties Comparison Apache Impala vs. ArcadeDB vs. SAP IQ vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Columnar RDBMS optimized for Big Data analytics

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

column-oriented

Key-value store

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.10
Rank	#358	Overall
	#48	Document stores
	#38	Graph DBMS
	#52	Key-value stores
	#35	Time Series DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

impala.apache.org

arcadedb.com

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

github.com/STSSoft/STSdb4

Technical documentation

impala.apache.org/impala-docs.html

docs.arcadedb.com

help.sap.com/docs/SAP_IQ

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Arcade Data

SAP, formerly Sybase

STS Soft SC

Initial release

2013

2021

1994

2011

Current release

4.1.0, June 2022

September 2021

16.1 SPS04, April 2019

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

Open Source

GPLv2, commercial license available

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

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
ODBC

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC
RESTful HTTP API

.NET Client API

Supported programming languages

All languages supporting JDBC/ODBC

Java

C
C#
C++
Java
Perl
PHP
Python
Ruby

C#
Java

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

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

SAP/Sybase Replication Server

none

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

relationship in graphs

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

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

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More resources

Recent citations in the news

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29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
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28 November 2017, Datanami

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

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17 August 2015, ComputerWeekly.com

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28 June 2022, Blocks & Files

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provided by Google News

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