DBMS > ObjectBox vs. OpenTSDB vs. Oracle Berkeley DB vs. Sadas Engine

System Properties Comparison ObjectBox vs. OpenTSDB vs. Oracle Berkeley DB vs. Sadas Engine

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Scalable Time Series DBMS based on HBase

Widely used in-process key-value store

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Object oriented DBMS
Vector DBMS

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector 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	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

github.com/objectbox
objectbox.io

opentsdb.net

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

www.sadasengine.com

Technical documentation

docs.objectbox.io

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

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

ObjectBox Limited

currently maintained by Yahoo and other contributors

Oracle

originally developed by Sleepycat, which was acquired by Oracle

SADAS s.r.l.

Initial release

2017

2011

1994

2006

Current release

4.0 (May 2024)

18.1.40, May 2020

8.0

License

Commercial or Open Source

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

LGPL

Open Source

commercial license available

commercial

free trial version available

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 and C++

Java

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

C++

Server operating systems

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

AIX
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes, plus "flex" map-like types

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

APIs and other access methods

Proprietary native API

HTTP API
Telnet API

JDBC
ODBC
Proprietary protocol

Supported programming languages

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Data sync between devices allowing occasional connected databases to work completely offline

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

Immediate 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

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

yes

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

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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

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

A real-time processing revival
1 April 2015, O'Reilly Media

provided by Google News

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

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

provided by Google News

Share this page