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DBMS > HarperDB vs. Hypertable vs. Postgres-XL vs. Sphinx

System Properties Comparison HarperDB vs. Hypertable vs. Postgres-XL vs. Sphinx

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Editorial information provided by DB-Engines
NameHarperDB  Xexclude from comparisonHypertable  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSphinx  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
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.An open source BigTable implementation based on distributed file systems such as HadoopBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeWide column storeRelational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.55
Rank#248  Overall
#38  Document stores
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.harperdb.iowww.postgres-xl.orgsphinxsearch.com
Technical documentationdocs.harperdb.io/­docswww.postgres-xl.org/­documentationsphinxsearch.com/­docs
DeveloperHarperDBHypertable Inc.Sphinx Technologies Inc.
Initial release201720092014 infosince 2012, originally named StormDB2001
Current release3.1, August 20210.9.8.11, March 201610 R1, October 20183.5.1, February 2023
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoGNU version 3. Commercial license availableOpen Source infoMozilla public licenseOpen Source infoGPL version 2, commercial licence available
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 languageNode.jsC++CC++
Server operating systemsLinux
OS X
Linux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemedynamic schemaschema-freeyesyes
Typing infopredefined data types such as float or dateyes infoJSON data typesnoyesno
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 infoXML type, but no XML query functionality
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like data manipulation statementsnoyes infodistributed, parallel query executionSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
C++ API
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocol
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
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresCustom Functions infosince release 3.1nouser defined functionsno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusterShardinghorizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infothe nodes on which a table resides can be definedselectable replication factor on file system levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACID infoMVCCno
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.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users and rolesnofine grained access rights according to SQL-standardno

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More resources
HarperDBHypertablePostgres-XLSphinx
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