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DBMS > HarperDB vs. Oracle Berkeley DB vs. Spark SQL vs. Sphinx vs. TerarkDB

System Properties Comparison HarperDB vs. Oracle Berkeley DB vs. Spark SQL vs. Sphinx vs. TerarkDB

Editorial information provided by DB-Engines
NameHarperDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonTerarkDB  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.Widely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databasesA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSSearch engineKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.55
Rank#248  Overall
#38  Document stores
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.harperdb.iowww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlsphinxsearch.comgithub.com/­bytedance/­terarkdb
Technical documentationdocs.harperdb.io/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docsbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperHarperDBOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationSphinx Technologies Inc.ByteDance, originally Terark
Initial release20171994201420012016
Current release3.1, August 202118.1.40, May 20203.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infocommercial license availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availablecommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageNode.jsC, Java, C++ (depending on the Berkeley DB edition)ScalaC++C++
Server operating systemsLinux
OS X
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemedynamic schemaschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyes infoJSON data typesnoyesnono
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.noyes infoonly with the Berkeley DB XML editionnono
Secondary indexesyesyesnoyes infofull-text index on all search fieldsno
SQL infoSupport of SQLSQL-like data manipulation statementsyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsSQL-like query language (SphinxQL)no
APIs and other access methodsJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
Proprietary protocolC++ API
Java API
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 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++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
Server-side scripts infoStored proceduresCustom Functions infosince release 3.1nononono
Triggersnoyes infoonly for the SQL APInonono
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusternoneyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infothe nodes on which a table resides can be definedSource-replica replicationnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, using LMDByesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlAccess rights for users and rolesnononono

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More resources
HarperDBOracle Berkeley DBSpark SQLSphinxTerarkDB
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