DBMS > IBM Db2 Event Store vs. Lovefield vs. SAP IQ vs. SiteWhere

System Properties Comparison IBM Db2 Event Store vs. Lovefield vs. SAP IQ vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Embeddable relational database for web apps written in pure JavaScript

Columnar RDBMS optimized for Big Data analytics

M2M integration platform for persisting/querying time series data

Primary database model

Event Store
Time Series DBMS

Relational DBMS

column-oriented

Time Series DBMS

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

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	3.27
Rank	#96	Overall
	#50	Relational DBMS

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Website

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

google.github.io/lovefield

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

github.com/sitewhere/sitewhere

Technical documentation

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

github.com/google/lovefield/blob/master/docs/spec_index.md

help.sap.com/docs/SAP_IQ

sitewhere1.sitewhere.io/index.html

Developer

IBM

Google

SAP, formerly Sybase

SiteWhere

Initial release

2017

2014

1994

2010

Current release

2.0

2.1.12, February 2017

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache 2.0

commercial

Open Source

Common Public Attribution License Version 1.0

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 and C++

JavaScript

Java

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

predefined scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

HTTP REST

Supported programming languages

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

JavaScript

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

shared disk or shared nothing architectures with SAP IQ Multiplexer

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

SAP/Sybase Replication Server

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

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

No - written data is immutable

yes

Durability

Support for making data persistent

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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