DBMS > OceanBase vs. OpenTSDB vs. Oracle Berkeley DB vs. PouchDB

System Properties Comparison OceanBase vs. OpenTSDB vs. Oracle Berkeley DB vs. PouchDB

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Editorial information provided by DB-Engines

Name

Description

A distributed, high available RDBMS compatible with Oracle and MySQL

Scalable Time Series DBMS based on HBase

Widely used in-process key-value store

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Relational DBMS

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

Secondary database models

Document store
Wide column store

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

Score	1.97
Rank	#119	Overall
	#58	Relational DBMS

Score	1.59
Rank	#140	Overall
	#12	Time Series DBMS

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Score	2.18
Rank	#114	Overall
	#21	Document stores

Website

en.oceanbase.com

opentsdb.net

www.oracle.com/database/technologies/related/berkeleydb.html

pouchdb.com

Technical documentation

en.oceanbase.com/docs/oceanbase-database

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

docs.oracle.com/cd/E17076_05/html/index.html

pouchdb.com/guides

Developer

OceanBase

previously Alibaba and Ant Group

currently maintained by Yahoo and other contributors

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Apache Software Foundation

Initial release

2010

2011

1994

2012

Current release

4.3.0, April 2024

18.1.40, May 2020

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Commercial license available

Open Source

LGPL

Open Source

commercial license available

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C, Java, C++ (depending on the Berkeley DB edition)

JavaScript

Server operating systems

Linux

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

via views

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

HTTP API
Telnet API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

Erlang
Go
Java
Python
R
Ruby

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

JavaScript

Server-side scripts

Stored procedures

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

View functions in JavaScript

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

Sharding

based on HBase

none

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

selectable replication factor

based on HBase

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

User concepts

Access control

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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