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DBMS > HarperDB vs. MaxDB vs. Oracle Berkeley DB vs. Spark SQL vs. SWC-DB

System Properties Comparison HarperDB vs. MaxDB vs. Oracle Berkeley DB vs. Spark SQL vs. SWC-DB

Editorial information provided by DB-Engines
NameHarperDB  Xexclude from comparisonMaxDB infoformerly named Adabas-D  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.A robust and reliable RDBMS optimized to run all major SAP solutionsWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMS
Primary database modelDocument storeRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSWide column store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.55
Rank#248  Overall
#38  Document stores
Score2.32
Rank#112  Overall
#55  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websitewww.harperdb.iomaxdb.sap.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.harperdb.io/­docsmaxdb.sap.com/­documentationdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHarperDBSAP, acquired from Software AG (Adabas-D) in 1997Oracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationAlex Kashirin
Initial release20171984199420142020
Current release3.1, August 20217.9.10.12, February 202418.1.40, May 20203.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercial infoLimited community edition freeOpen Source infocommercial license availableOpen Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageNode.jsC++C, Java, C++ (depending on the Berkeley DB edition)ScalaC++
Server operating systemsLinux
OS X
AIX
HP-UX
Linux
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Linux
Data schemedynamic schemayesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes infoJSON data typesyesnoyes
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.nonoyes infoonly with the Berkeley DB XML editionnono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like data manipulation statementsyesyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
ADO.NET
JDBC
ODBC
WebDAV
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languages.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
.Net
C#
Java
Perl
PHP
Python
.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++
Server-side scripts infoStored proceduresCustom Functions infosince release 3.1yesnonono
Triggersnoyesyes infoonly for the SQL APInono
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusternonenoneyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infothe nodes on which a table resides can be definedSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, using LMDByesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesnono
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardnono

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More resources
HarperDBMaxDB infoformerly named Adabas-DOracle Berkeley DBSpark SQLSWC-DB infoSuper Wide Column Database
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