DBMS > Axibase vs. Badger vs. IBM Cloudant vs. IBM Db2 Event Store

System Properties Comparison Axibase vs. Badger vs. IBM Cloudant vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Database as a Service offering based on Apache CouchDB

Distributed Event Store optimized for Internet of Things use cases

Primary database model

Time Series DBMS

Key-value store

Document store

Event Store
Time Series DBMS

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

Score	0.21
Rank	#308	Overall
	#25	Time Series DBMS

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	2.85
Rank	#95	Overall
	#18	Document stores

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Website

axibase.com/docs/atsd/finance

github.com/dgraph-io/badger

www.ibm.com/products/cloudant

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

Technical documentation

godoc.org/github.com/dgraph-io/badger

cloud.ibm.com/docs/Cloudant

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

Developer

Axibase Corporation

DGraph Labs

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

IBM

Initial release

2013

2017

2010

2017

Current release

15585

2.0

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache 2.0

commercial

free developer edition available

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

Java

Erlang

C and C++

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

hosted

Linux

Linux, macOS, Windows for the developer addition

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

SQL-like query language

yes

through the embedded Spark runtime

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

Server-side scripts

Stored procedures

yes

View functions (Map-Reduce) in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
Source-replica replication

Active-active shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

No - written data is immutable

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

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 can be defined per database

fine grained access rights according to SQL-standard

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