DBMS > IBM Cloudant vs. OpenTenBase vs. OpenTSDB vs. Spark SQL

System Properties Comparison IBM Cloudant vs. OpenTenBase vs. OpenTSDB vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

An enterprise-level distributed HTAP open source database based on PostgreSQL

Scalable Time Series DBMS based on HBase

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

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

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.08
Rank	#370	Overall
	#156	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

www.ibm.com/products/cloudant

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

opentsdb.net

spark.apache.org/sql

Technical documentation

cloud.ibm.com/docs/Cloudant

docs.opentenbase.org
docs.opentenbase.org/en

opentsdb.net/docs/build/html/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

OpenAtom Foundation, previously Tencent

currently maintained by Yahoo and other contributors

Apache Software Foundation

Initial release

2010

2011

2014

Current release

2.5, January 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

BSD-3

Open Source

LGPL

Open Source

Apache 2.0

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

Erlang

Java

Scala

Server operating systems

hosted

Linux

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

yes

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP/JSON API

HTTP API
Telnet API

JDBC
ODBC

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
Go
Java
PHP
Python

Erlang
Go
Java
Python
R
Ruby

Java
Python
R
Scala

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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.

User concepts

Access control

Access rights for users can be defined per database

Access rights for users, groups and roles according to SQL-standard

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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