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DBMS > Blueflood vs. SiteWhere vs. Spark SQL vs. Teradata

System Properties Comparison Blueflood vs. SiteWhere vs. Spark SQL vs. Teradata

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Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraM2M integration platform for persisting/querying time series dataSpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#353  Overall
#34  Time Series DBMS
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websiteblueflood.iogithub.com/­sitewhere/­sitewherespark.apache.org/­sqlwww.teradata.com
Technical documentationgithub.com/­rax-maas/­blueflood/­wikisitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperRackspaceSiteWhereApache Software FoundationTeradata
Initial release2013201020141984
Current release3.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoCommon Public Attribution License Version 1.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaScala
Server operating systemsLinux
OS X
Linux
OS X
Windows
Linux
OS X
Windows
hosted
Linux
Data schemepredefined schemepredefined schemeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononoyes
Secondary indexesnononoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsHTTP RESTHTTP RESTJDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesJava
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnonoyes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding infobased on HBaseyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandraselectable replication factor infobased on HBasenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlnoUsers with fine-grained authorization conceptnofine grained access rights according to SQL-standard

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More resources
BluefloodSiteWhereSpark SQLTeradata
DB-Engines blog posts

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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