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DBMS > OpenTSDB vs. Spark SQL vs. Yaacomo

System Properties Comparison OpenTSDB vs. Spark SQL vs. Yaacomo

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Editorial information provided by DB-Engines
NameOpenTSDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionScalable Time Series DBMS based on HBaseSpark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelTime Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.68
Rank#146  Overall
#12  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteopentsdb.netspark.apache.org/­sqlyaacomo.com
Technical documentationopentsdb.net/­docs/­build/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
Developercurrently maintained by Yahoo and other contributorsApache Software FoundationQ2WEB GmbH
Initial release201120142009
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoLGPLOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemsLinux
Windows
Linux
OS X
Windows
Android
Linux
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenumeric data for metrics, strings for tagsyesyes
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
Secondary indexesnonoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes
APIs and other access methodsHTTP API
Telnet API
JDBC
ODBC
JDBC
ODBC
Supported programming languagesErlang
Go
Java
Python
R
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnono
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on HBaseyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on HBasenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infobased on HBaseImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standard

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More resources
OpenTSDBSpark SQLYaacomo
DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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