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DBMS > Amazon Redshift vs. Kinetica vs. Microsoft Azure Table Storage vs. RocksDB vs. Spark SQL

System Properties Comparison Amazon Redshift vs. Kinetica vs. Microsoft Azure Table Storage vs. RocksDB vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRocksDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsFully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasetsEmbeddable 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 DBMSRelational DBMSWide column storeKey-value storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score3.65
Rank#85  Overall
#11  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­redshiftwww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tablesrocksdb.orgspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­redshiftdocs.kinetica.comgithub.com/­facebook/­rocksdb/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazon (based on PostgreSQL)KineticaMicrosoftFacebook, Inc.Apache Software Foundation
Initial release20122012201220132014
Current release7.1, August 20218.11.4, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC, C++C++Scala
Server operating systemshostedLinuxhostedLinuxLinux
OS X
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonononono
Secondary indexesrestrictedyesnonono
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL-like DML and DDL statementsnonoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIC++ API
Java API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
Perl
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Pythonuser defined functionsnonono
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingyesno
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.yesyes infoGPU vRAM or System RAMnoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelAccess rights based on private key authentication or shared access signaturesnono

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3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
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Speedb: A high performance RocksDB-compliant key-value store optimized for write-intensive workloads.
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More resources
Amazon RedshiftKineticaMicrosoft Azure Table StorageRocksDBSpark SQL
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