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DBMS > Amazon Redshift vs. Ingres vs. Kinetica vs. RocksDB vs. Spark SQL

System Properties Comparison Amazon Redshift vs. Ingres vs. Kinetica vs. RocksDB vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonIngres  Xexclude from comparisonKinetica  Xexclude from comparisonRocksDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsWell established RDBMSFully vectorized database across both GPUs and CPUsEmbeddable 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 DBMSRelational DBMSKey-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
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score3.65
Rank#85  Overall
#11  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­redshiftwww.actian.com/­databases/­ingreswww.kinetica.comrocksdb.orgspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­redshiftdocs.actian.com/­ingresdocs.kinetica.comgithub.com/­facebook/­rocksdb/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazon (based on PostgreSQL)Actian CorporationKineticaFacebook, Inc.Apache Software Foundation
Initial release20121974 infooriginally developed at University Berkely in early 1970s201220132014
Current release11.2, May 20227.1, 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 serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCCC, C++C++Scala
Server operating systemshostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
LinuxLinuxLinux
OS X
Windows
Data schemeyesyesyesschema-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.nono infobut tools for importing/exporting data from/to XML-files availablenonono
Secondary indexesrestrictedyesyesnono
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardyesSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
ODBC
RESTful HTTP API
C++ API
Java API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
Perl
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Pythonyesuser defined functionsnono
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesIngres ReplicatorSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoyesno
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyesyes
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 RAMyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users and roles on table levelnono

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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 RedshiftIngresKineticaRocksDBSpark SQL
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