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DBMS > EsgynDB vs. HBase vs. RocksDB vs. Spark SQL

System Properties Comparison EsgynDB vs. HBase vs. RocksDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonHBase  Xexclude from comparisonRocksDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionWide-column store based on Apache Hadoop and on concepts of BigTableEmbeddable persistent key-value store optimized for fast storage (flash and RAM)Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSWide column storeKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.26
Rank#311  Overall
#141  Relational DBMS
Score31.60
Rank#26  Overall
#2  Wide column stores
Score4.52
Rank#80  Overall
#10  Key-value stores
Score19.56
Rank#34  Overall
#21  Relational DBMS
Websitewww.esgyn.cnhbase.apache.orgrocksdb.orgspark.apache.org/­sql
Technical documentationhbase.apache.org/­book.htmlgithub.com/­facebook/­rocksdb/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynApache Software Foundation infoApache top-level project, originally developed by PowersetFacebook, Inc.Apache Software Foundation
Initial release2015200820132014
Current release2.3.4, January 20218.10.0, December 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaC++Scala
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
LinuxLinux
OS X
Windows
Data schemeyesschema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROnoyes
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.nononono
Secondary indexesyesnonono
SQL infoSupport of SQLyesnonoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
Java API
RESTful HTTP API
Thrift
C++ API
Java API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Groovy
Java
PHP
Python
Scala
C
C++
Go
Java
Perl
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresyes infoCoprocessors in Javanono
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replication
Source-replica replication
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)yesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnono

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More resources
EsgynDBHBaseRocksDBSpark SQL
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