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DBMS > Google Cloud Spanner vs. Riak TS vs. Sadas Engine vs. Spark SQL vs. VictoriaMetrics

System Properties Comparison Google Cloud Spanner vs. Riak TS vs. Sadas Engine vs. Spark SQL vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonRiak TS  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KVSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processingA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitecloud.google.com/­spannerwww.sadasengine.comspark.apache.org/­sqlvictoriametrics.com
Technical documentationcloud.google.com/­spanner/­docswww.tiot.jp/­riak-docs/­riak/­ts/­latestwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperGoogleOpen Source, formerly Basho TechnologiesSADAS s.r.l.Apache Software FoundationVictoriaMetrics
Initial release20172015200620142018
Current release3.0.0, September 20228.03.5.0 ( 2.13), September 2023v1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Sourcecommercial infofree trial version availableOpen Source infoApache 2.0Open Source infoApache Version 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 languageErlangC++ScalaGo
Server operating systemshostedLinux
OS X
AIX
Linux
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 indexesyesrestrictedyesno
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011yes, limitedyesSQL-like DML and DDL statementsno
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP API
Native Erlang Interface
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoErlangnonono
Triggersnoyes infopre-commit hooks and post-commit hooksnonono
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 with 3 replicas for regional instances.selectable replication factornonenoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno infolinks between datasets can be storedyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationnonono
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.noyes infomanaged by 'Learn by Usage'nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users, groups and roles according to SQL-standardno

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More resources
Google Cloud SpannerRiak TSSadas EngineSpark SQLVictoriaMetrics
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