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DBMS > HarperDB vs. Oracle Berkeley DB vs. Spark SQL vs. TerarkDB vs. Warp 10

System Properties Comparison HarperDB vs. Oracle Berkeley DB vs. Spark SQL vs. TerarkDB vs. Warp 10

Editorial information provided by DB-Engines
NameHarperDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparisonWarp 10  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 processingA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDBTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSKey-value storeTime Series DBMS
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
Score0.00
Rank#383  Overall
#60  Key-value stores
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitewww.harperdb.iowww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­bytedance/­terarkdbwww.warp10.io
Technical documentationdocs.harperdb.io/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKcwww.warp10.io/­content/­02_Getting_started
DeveloperHarperDBOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationByteDance, originally TerarkSenX
Initial release20171994201420162015
Current release3.1, August 202118.1.40, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infocommercial license availableOpen Source infoApache 2.0commercial inforestricted open source version availableOpen Source infoApache License 2.0
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++Java
Server operating systemsLinux
OS X
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemedynamic schemaschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes infoJSON data typesnoyesnoyes
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 editionnonono
Secondary indexesyesyesnonono
SQL infoSupport of SQLSQL-like data manipulation statementsyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsnono
APIs and other access methodsJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
C++ API
Java API
HTTP API
Jupyter
WebSocket
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++
Java
Server-side scripts infoStored proceduresCustom Functions infosince release 3.1nononoyes infoWarpScript
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 CorenoneSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes infothe nodes on which a table resides can be definedSource-replica replicationnonenoneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infobased on HBase
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 LMDByesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyesyes
User concepts infoAccess controlAccess rights for users and rolesnononoMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
HarperDBOracle Berkeley DBSpark SQLTerarkDBWarp 10
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