DBMS > Apache Impala vs. IBM Db2 Event Store vs. SAP IQ vs. SQLite vs. Warp 10

System Properties Comparison Apache Impala vs. IBM Db2 Event Store vs. SAP IQ vs. SQLite vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Distributed Event Store optimized for Internet of Things use cases

Columnar RDBMS optimized for Big Data analytics

Widely used embeddable, in-process RDBMS

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Relational DBMS

column-oriented

Relational DBMS

Time Series DBMS

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	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

impala.apache.org

www.ibm.com/products/db2-event-store

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

www.sqlite.org

www.warp10.io

Technical documentation

impala.apache.org/impala-docs.html

www.ibm.com/docs/en/db2-event-store

help.sap.com/docs/SAP_IQ

www.sqlite.org/docs.html

www.warp10.io/content/02_Getting_started

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

IBM

SAP, formerly Sybase

Dwayne Richard Hipp

SenX

Initial release

2013

2017

1994

2000

2015

Current release

4.1.0, June 2022

2.0

16.1 SPS04, April 2019

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free developer edition available

commercial

Open Source

Public Domain

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Java

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

AIX
HP-UX
Linux
Solaris
Windows

server-less

Linux
OS X
Windows

Data scheme

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

through the embedded Spark runtime

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C
C#
C++
Java
Perl
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Active-active shard replication

SAP/Sybase Replication Server

none

selectable replication factor

based on HBase

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

based on HBase

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

No - written data is immutable

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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