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

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

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonKinetica  Xexclude from comparisonPrometheus  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 CPUsOpen-source Time Series DBMS and monitoring systemEmbeddable 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 DBMSTime Series 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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score3.65
Rank#85  Overall
#11  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­redshiftwww.kinetica.comprometheus.iorocksdb.orgspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­redshiftdocs.kinetica.comprometheus.io/­docsgithub.com/­facebook/­rocksdb/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazon (based on PostgreSQL)KineticaFacebook, Inc.Apache Software Foundation
Initial release20122012201520132014
Current release7.1, August 20218.11.4, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC, C++GoC++Scala
Server operating systemshostedLinuxLinux
Windows
LinuxLinux
OS X
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlynoyes
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 infoImport of XML data possiblenono
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/JSON APIC++ API
Java API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
JavaScript (Node.js)
Python
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
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 nodesShardingShardingShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoby Federationyesnone
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 configurationnone
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoyesno
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 levelnonono

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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 RedshiftKineticaPrometheusRocksDBSpark SQL
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