DBMS > Apache Druid vs. Couchbase vs. VoltDB vs. Yanza

System Properties Comparison Apache Druid vs. Couchbase vs. VoltDB vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS
Time Series DBMS

Document store

Relational DBMS

Time Series 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	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

druid.apache.org

www.couchbase.com

www.voltdb.com

yanza.com

Technical documentation

druid.apache.org/docs/latest/design

docs.couchbase.com

docs.voltdb.com

Developer

Apache Software Foundation and contributors

Couchbase, Inc.

VoltDB Inc.

Yanza

Initial release

2012

2011

2010

2015

Current release

29.0.1, April 2024

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

11.3, April 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

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C, C++, Go and Erlang

Java, C++

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

Linux
OS X

for development

Windows

Data scheme

yes

schema-less columns are supported

schema-free

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

yes

only a subset of SQL 99

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

Java API
JDBC
RESTful HTTP/JSON API

HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

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

Java

Triggers

yes

via the TAP protocol

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Automatic Sharding

Sharding

none

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

Multi-source replication
Source-replica replication

none

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

Immediate Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Snapshots and command logging

yes

In-memory capabilities

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

yes

Ephemeral buckets

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.

Users and roles with access to stored procedures

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