DBMS > Apache Phoenix vs. BaseX vs. Couchbase vs. KairosDB vs. Rockset

System Properties Comparison Apache Phoenix vs. BaseX vs. Couchbase vs. KairosDB vs. Rockset

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

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

Distributed Time Series DBMS based on Cassandra or H2

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

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

Relational DBMS
Search engine

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

phoenix.apache.org

basex.org

www.couchbase.com

github.com/kairosdb/kairosdb

rockset.com

Technical documentation

Developer

Apache Software Foundation

BaseX GmbH

Couchbase, Inc.

Rockset

Initial release

2014

2007

2011

2013

2019

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

10.7, August 2023

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

1.2.2, November 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD license

Open Source

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

Open Source

Apache 2.0

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

C++

Server operating systems

Linux
Unix
Windows

Linux
OS X
Windows

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

Typing

predefined data types such as float or date

yes

XQuery supports types

yes

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

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

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

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

Graphite protocol
HTTP REST
Telnet API

HTTP REST

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java
JavaScript

Node.js
PHP
Python

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

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

Triggers

yes

via events

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic Sharding

Sharding

based on Cassandra

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Multi-source replication

including cross data center replication
Source-replica replication

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Users with fine-grained authorization concept on 4 levels

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

simple password-based access control

Access rights for users and organizations can be defined via Rockset console

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