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DBMS > Brytlyt vs. HarperDB vs. Hive vs. Sphinx

System Properties Comparison Brytlyt vs. HarperDB vs. Hive vs. Sphinx

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonHarperDB  Xexclude from comparisonHive  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLUltra-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.data warehouse software for querying and managing large distributed datasets, built on HadoopOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSDocument storeRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score0.60
Rank#244  Overall
#38  Document stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitebrytlyt.iowww.harperdb.iohive.apache.orgsphinxsearch.com
Technical documentationdocs.brytlyt.iodocs.harperdb.io/­docscwiki.apache.org/­confluence/­display/­Hive/­Homesphinxsearch.com/­docs
DeveloperBrytlytHarperDBApache Software Foundation infoinitially developed by FacebookSphinx Technologies Inc.
Initial release2016201720122001
Current release5.0, August 20233.1, August 20213.1.3, April 20223.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ and CUDANode.jsJavaC++
Server operating systemsLinux
OS X
Windows
Linux
OS X
All OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesdynamic schemayesyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesno
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 infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesSQL-like data manipulation statementsSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
Thrift
Proprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.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
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLCustom Functions infosince release 3.1yes infouser defined functions and integration of map-reduceno
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusterShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infothe nodes on which a table resides can be definedselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes 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.yes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and rolesAccess rights for users, groups and rolesno

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