DBMS > IBM Db2 Event Store vs. Microsoft Azure Cosmos DB vs. Quasardb vs. Tkrzw vs. Yaacomo

System Properties Comparison IBM Db2 Event Store vs. Microsoft Azure Cosmos DB vs. Quasardb vs. Tkrzw vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Distributed Event Store optimized for Internet of Things use cases

Globally distributed, horizontally scalable, multi-model database service

Distributed, high-performance timeseries database

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Event Store
Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial 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

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

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

azure.microsoft.com/services/cosmos-db

quasar.ai

dbmx.net/tkrzw

yaacomo.com

Technical documentation

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

learn.microsoft.com/azure/cosmos-db

doc.quasar.ai/master

Developer

IBM

Microsoft

quasardb

Mikio Hirabayashi

Q2WEB GmbH

Initial release

2017

2014

2009

2020

2009

Current release

2.0

3.14.1, January 2024

0.9.3, August 2020

License

Commercial or Open Source

commercial

free developer edition available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

hosted

BSD
Linux
OS X
Windows

Linux
macOS

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

integer and binary

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

All properties auto-indexed by default

yes

with tags

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like query language

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP API

JDBC
ODBC

Supported programming languages

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes

Implicit feature of the cloud service

Source-replica replication with selectable replication factor

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

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 LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

using specific database classes

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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