DBMS > EXASOL vs. IBM Db2 Event Store vs. WakandaDB vs. YottaDB

System Properties Comparison EXASOL vs. IBM Db2 Event Store vs. WakandaDB vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Distributed Event Store optimized for Internet of Things use cases

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Object oriented DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

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

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

www.exasol.com

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

wakanda.github.io

yottadb.com

Technical documentation

www.exasol.com/resources

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

wakanda.github.io/doc

yottadb.com/resources/documentation

Developer

Exasol

IBM

Wakanda SAS

YottaDB, LLC

Initial release

2000

2017

2012

2001

Current release

2.0

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

free developer edition available

Open Source

AGPLv3, extended commercial license available

Open Source

AGPL 3.0

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++

C++, JavaScript

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Windows

Docker
Linux

Data scheme

yes

schema-free

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

by using the Octo plugin

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

Java
Lua
Python
R

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

JavaScript

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

optimistic locking

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

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

yes

Users and groups based on OS-security mechanisms

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