DBMS > Drizzle vs. IBM Db2 Event Store vs. ToroDB vs. Trafodion

System Properties Comparison Drizzle vs. IBM Db2 Event Store vs. ToroDB vs. Trafodion

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Distributed Event Store optimized for Internet of Things use cases

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Document store

Relational DBMS

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

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

Website

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

github.com/torodb/server

trafodion.apache.org

Technical documentation

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

trafodion.apache.org/documentation.html

Developer

Drizzle project, originally started by Brian Aker

IBM

8Kdata

Apache Software Foundation, originally developed by HP

Initial release

2008

2017

2016

2014

Current release

7.2.4, September 2012

2.0

2.3.0, February 2019

License

Commercial or Open Source

Open Source

GNU GPL

commercial

free developer edition available

Open Source

AGPL-V3

Open Source

Apache 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

C++, Java

Server operating systems

FreeBSD
Linux
OS X

Linux

Linux, macOS, Windows for the developer addition

All OS with a Java 7 VM

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

with proprietary extensions

yes

through the embedded Spark runtime

yes

APIs and other access methods

JDBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

C
C++
Java
PHP

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Active-active shard replication

Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate 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

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

In-memory capabilities

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

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Access rights for users and roles

fine grained access rights according to SQL-standard

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