DBMS > OpenTSDB vs. Oracle Berkeley DB vs. SQL.JS vs. SwayDB

System Properties Comparison OpenTSDB vs. Oracle Berkeley DB vs. SQL.JS vs. SwayDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Scalable Time Series DBMS based on HBase

Widely used in-process key-value store

Port of SQLite to JavaScript

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

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

Relational DBMS

Key-value store

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

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	0.53
Rank	#246	Overall
	#115	Relational DBMS

Score	0.00
Rank	#384	Overall
	#60	Key-value stores

Website

opentsdb.net

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

sql.js.org

swaydb.simer.au

Technical documentation

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

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

sql.js.org/documentation/index.html

Developer

currently maintained by Yahoo and other contributors

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Alon Zakai

enhancements implemented by others

Simer Plaha

Initial release

2011

1994

2012

2018

Current release

18.1.40, May 2020

License

Commercial or Open Source

Open Source

LGPL

Open Source

commercial license available

Open Source

GNU Affero GPL V3.0

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

Java

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

JavaScript

Scala

Server operating systems

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

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

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API
Telnet API

JavaScript 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

JavaScript

Java
Kotlin
Scala

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

selectable replication factor

based on HBase

Source-replica replication

none

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

except by serializing a db to a file

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

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

show all

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

show all

Recent citations in the 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

provided by Google News

ACM recognizes far-reaching technical achievements with special awards
26 May 2021, EurekAlert

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

How to store financial market data for backtesting
26 January 2019, Towards Data Science

provided by Google News

9 Best JavaScript and TypeScript ORMs for 2024
22 March 2023, SitePoint

SQLite On The Web: Absurd-sql
24 August 2021, Hackaday

Running PostgreSQL Inside Your Browser
8 September 2022, iProgrammer

React Native for beginners
31 October 2018, hackernoon.com

10 Low-Code Rules for Serious Coders
21 November 2022, Embedded Computing Design

provided by Google News

Share this page