DBMS > Oracle Berkeley DB vs. Rockset vs. SiteWhere vs. Transbase vs. XTDB

System Properties Comparison Oracle Berkeley DB vs. Rockset vs. SiteWhere vs. Transbase vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Widely used in-process key-value store

A scalable, reliable search and analytics service in the cloud, built on RocksDB

M2M integration platform for persisting/querying time series data

A resource-optimized, high-performance, universally applicable RDBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Relational DBMS
Search engine

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

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

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

rockset.com

github.com/sitewhere/sitewhere

www.transaction.de/en/products/transbase.html

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

docs.rockset.com

sitewhere1.sitewhere.io/index.html

www.transaction.de/en/products/transbase/features.html

www.xtdb.com/docs

Developer

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Rockset

SiteWhere

Transaction Software GmbH

Juxt Ltd.

Initial release

1994

2019

2010

1987

2019

Current release

18.1.40, May 2020

Transbase 8.3, 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

commercial license available

commercial

Open Source

Common Public Attribution License Version 1.0

commercial

free development license

Open Source

MIT License

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

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

C++

Java

C and C++

Clojure

Server operating systems

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

hosted

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

predefined scheme

yes

schema-free

Typing

predefined data types such as float or date

dynamic typing

yes

yes, extensible-data-notation format

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

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

Read-only SQL queries, including JOINs

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP REST

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST
JDBC

Supported programming languages

.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

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

selectable replication factor

based on HBase

Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 and organizations can be defined via Rockset console

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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