DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > FatDB vs. Oracle Berkeley DB vs. Spark SQL vs. Transbase

System Properties Comparison FatDB vs. Oracle Berkeley DB vs. Spark SQL vs. Transbase

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Widely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelDocument store
Key-value store
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperFatCloudOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationTransaction Software GmbH
Initial release2012199420141987
Current release18.1.40, May 20203.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infocommercial license availableOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C, Java, C++ (depending on the Berkeley DB edition)ScalaC and C++
Server operating systemsWindowsAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yes infoonly with the Berkeley DB XML editionnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLno infoVia inetgration in SQL Serveryes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsyes
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC#.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infovia applicationsnonoyes
Triggersyes infovia applicationsyes infoonly for the SQL APInoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsnonofine grained access rights according to SQL-standard

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
FatDBOracle Berkeley DBSpark SQLTransbase
Recent citations in the news

Margo Seltzer Named ACM Athena Lecturer for Technical and Mentoring Contributions
26 April 2023, HPCwire

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

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

A Quick Look at Open Source Databases for Mobile App Development
29 April 2018, Open Source For You

Motorola A780 Linux based smartphone to have mobile database
14 September 2004, Geekzone

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 2024, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

provided by Google News



Share this page

Featured Products

SingleStore logo

The database to transact, analyze and contextualize your data in real time.
Try it today.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here