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DBMS > HBase vs. Immudb vs. Kinetica vs. Microsoft Azure SQL Database vs. Spark SQL

System Properties Comparison HBase vs. Immudb vs. Kinetica vs. Microsoft Azure SQL Database vs. Spark SQL

Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonImmudb  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionWide-column store based on Apache Hadoop and on concepts of BigTableAn open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.Fully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeKey-value storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.24
Rank#305  Overall
#43  Key-value stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitehbase.apache.orggithub.com/­codenotary/­immudb
immudb.io
www.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasespark.apache.org/­sql
Technical documentationhbase.apache.org/­book.htmldocs.immudb.iodocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetCodenotaryKineticaMicrosoftApache Software Foundation
Initial release20082020201220102014
Current release2.3.4, January 20211.2.3, April 20227.1, August 2021V123.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC, C++C++Scala
Server operating systemsLinux
Unix
Windows infousing Cygwin
BSD
Linux
macOS
Solaris
Windows
z/OS
LinuxhostedLinux
OS X
Windows
Data schemeschema-free, schema definition possibleschema-freeyesyesyes
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyesyesyes
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.nononoyesno
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnoSQL-like syntaxSQL-like DML and DDL statementsyesSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP API
Thrift
gRPC protocol
PostgreSQL wire protocol
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoCoprocessors in Javanouser defined functionsTransact SQLno
Triggersyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationyes, with always 3 replicas availablenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)ACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users and roles on table levelfine grained access rights according to SQL-standardno

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More resources
HBaseImmudbKineticaMicrosoft Azure SQL Database infoformerly SQL AzureSpark SQL
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