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

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

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Editorial information provided by DB-Engines

Name

Description

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Scalable Time Series DBMS based on HBase

Widely used in-process key-value store

A managed, cloud-native vector database

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

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

Score	0.00
Rank	#385	Overall
	#40	Time Series 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	3.02
Rank	#87	Overall
	#3	Vector DBMS

Website

www.opengemini.org
github.com/openGemini

opentsdb.net

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

www.pinecone.io

Technical documentation

docs.opengemini.org/guide

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

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

docs.pinecone.io/docs/overview

Developer

Huawei and openGemini community

currently maintained by Yahoo and other contributors

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Pinecone Systems, Inc

Initial release

2022

2011

1994

2019

Current release

1.1, July 2023

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

LGPL

Open Source

commercial license available

commercial

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

Java

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

Server operating systems

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

hosted

Data scheme

schema-free

Typing

predefined data types such as float or date

Integer, Float, Boolean, String

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

SQL-like query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

HTTP REST

HTTP API
Telnet API

RESTful HTTP API

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

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

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

Source-replica replication

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

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

Administrators and common users accounts

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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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Vector databases
2 June 2023, Matthias Gelbmann

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Recent citations in the news

Open Source @ Huawei
9 February 2022, Huawei

provided by Google News

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

Brain Monitoring with Kafka, OpenTSDB, and Grafana
5 August 2016, KDnuggets

LogicMonitor Rolls a Time Series Database for Finer-Grain Reporting
1 June 2016, The New Stack

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1 April 2015, O'Reilly Media

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What is NoSQL (Not Only SQL database)?
28 February 2022, TechTarget

Margo I. Seltzer
18 August 2020, Berkman Klein Center

Oracle acquires Sleepycat for code
17 August 2016, East Bay Times

Database Trends Report: SQL Beats NoSQL, MySQL Most Popular
5 March 2019, ADT Magazine

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26 January 2019, Towards Data Science

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27 August 2024, VentureBeat

Using the Pinecone vector database in .NET
12 September 2024, InfoWorld

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