DBMS > Apache Druid vs. BigObject vs. IBM Db2 Event Store vs. KairosDB

System Properties Comparison Apache Druid vs. BigObject vs. IBM Db2 Event Store vs. KairosDB

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Analytic DBMS for real-time computations and queries

Distributed Event Store optimized for Internet of Things use cases

Distributed Time Series DBMS based on Cassandra or H2

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Event Store
Time Series DBMS

Time Series DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

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

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Website

druid.apache.org

bigobject.io

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

github.com/kairosdb/kairosdb

Technical documentation

druid.apache.org/docs/latest/design

docs.bigobject.io

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

kairosdb.github.io

Developer

Apache Software Foundation and contributors

BigObject, Inc.

IBM

Initial release

2012

2015

2017

2013

Current release

29.0.1, April 2024

2.0

1.2.2, November 2018

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free community edition available

commercial

free developer edition available

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

Java

C and C++

Java

Server operating systems

Linux
OS X
Unix

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

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

SQL for querying

SQL-like DML and DDL statements

yes

through the embedded Spark runtime

APIs and other access methods

JDBC
RESTful HTTP/JSON API

fluentd
ODBC
RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Lua

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

Active-active shard replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

simple password-based access control

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