DBMS > Apache Druid vs. Couchbase vs. Ehcache vs. IBM Db2 warehouse

System Properties Comparison Apache Druid vs. Couchbase vs. Ehcache vs. IBM Db2 warehouse

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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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

A widely adopted Java cache with tiered storage options

Cloud-based data warehousing service

Primary database model

Relational DBMS
Time Series DBMS

Document store

Key-value store

Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Website

druid.apache.org

www.couchbase.com

www.ehcache.org

www.ibm.com/products/db2/warehouse

Technical documentation

druid.apache.org/docs/latest/design

docs.couchbase.com

www.ehcache.org/documentation

Developer

Apache Software Foundation and contributors

Couchbase, Inc.

Terracotta Inc, owned by Software AG

IBM

Initial release

2012

2011

2009

2014

Current release

29.0.1, April 2024

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

3.10.0, March 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache Version 2; commercial licenses available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++, Go and Erlang

Java

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

All OS with a Java VM

hosted

Data scheme

yes

schema-less columns are supported

schema-free

yes

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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

JCache

.NET Client API
JDBC
ODBC
OLE DB

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

PL/SQL, SQL PL

Triggers

yes

via the TAP protocol

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Automatic Sharding

Sharding

by using Terracotta Server

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication

including cross data center replication
Source-replica replication

yes

by using Terracotta Server

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

User concepts

Access control

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

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

fine grained access rights according to SQL-standard

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