DBMS > OpenTSDB vs. Oracle Berkeley DB vs. Pinecone vs. RocksDB

System Properties Comparison OpenTSDB vs. Oracle Berkeley DB vs. Pinecone vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Scalable Time Series DBMS based on HBase

Widely used in-process key-value store

A managed, cloud-native vector database

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Vector DBMS

Key-value store

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

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

opentsdb.net

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

www.pinecone.io

rocksdb.org

Technical documentation

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

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

docs.pinecone.io/docs/overview

github.com/facebook/rocksdb/wiki

Developer

currently maintained by Yahoo and other contributors

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Pinecone Systems, Inc

Facebook, Inc.

Initial release

2011

1994

2019

2013

Current release

18.1.40, May 2020

9.2.1, May 2024

License

Commercial or Open Source

Open Source

LGPL

Open Source

commercial license available

commercial

Open Source

BSD

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

C++

Server operating systems

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

hosted

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

numeric data for metrics, strings for tags

String, Number, Boolean

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

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

HTTP API
Telnet API

RESTful HTTP API

C++ API
Java API

Supported programming languages

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

Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on HBase

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

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

User concepts

Access control

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