DBMS > Graphite vs. IBM Db2 Event Store vs. JSqlDb vs. SAP IQ

System Properties Comparison Graphite vs. IBM Db2 Event Store vs. JSqlDb vs. SAP IQ

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Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Distributed Event Store optimized for Internet of Things use cases

JavaScript Query Language Database, stores JavaScript objects and primitives

Columnar RDBMS optimized for Big Data analytics

Primary database model

Time Series DBMS

Event Store
Time Series DBMS

Document store
Object oriented DBMS

Relational DBMS

column-oriented

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

Score	4.75
Rank	#75	Overall
	#5	Time Series DBMS

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

Score	3.27
Rank	#96	Overall
	#50	Relational DBMS

Website

github.com/graphite-project/graphite-web

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

jsqldb.org (offline)

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

Technical documentation

graphite.readthedocs.io

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

help.sap.com/docs/SAP_IQ

Developer

Chris Davis

IBM

Konrad von Backstrom

SAP, formerly Sybase

Initial release

2006

2017

2018

1994

Current release

2.0

0.8, December 2018

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free developer edition available

Open Source

commercial

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

Python

C and C++

Server operating systems

Linux
Unix

Linux

Linux, macOS, Windows for the developer addition

Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

Numeric data only

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

yes

APIs and other access methods

HTTP API
Sockets

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

JavaScript (Node.js)
Python

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

functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

none

Active-active shard replication

none

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

locking

No - written data is immutable

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

using RocksDB

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

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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