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DBMS > Hypertable vs. Realm vs. Spark SQL vs. TigerGraph

System Properties Comparison Hypertable vs. Realm vs. Spark SQL vs. TigerGraph

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonRealm  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataSpark SQL is a component on top of 'Spark Core' for structured data processingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelWide column storeDocument storeRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.41
Rank#52  Overall
#8  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websiterealm.iospark.apache.org/­sqlwww.tigergraph.com
Technical documentationrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
DeveloperHypertable Inc.Realm, acquired by MongoDB in May 2019Apache Software Foundation
Initial release2009201420142017
Current release0.9.8.11, March 20163.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen SourceOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Android
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nonono
Secondary indexesrestricted infoonly exact value or prefix value scansyesno
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsC++ API
Thrift
JDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
.Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnono inforuns within the applications so server-side scripts are unnecessarynoyes
Triggersnoyes infoChange Listenersnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoIn-Memory realmnono
User concepts infoAccess controlnoyesnoRole-based access control

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More resources
HypertableRealmSpark SQLTigerGraph
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