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

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

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Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  Xexclude from comparisonYDB  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 distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSDocument store
Relational 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
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websiteblueflood.iogithub.com/­sitewhere/­sitewherespark.apache.org/­sqlgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationgithub.com/­rax-maas/­blueflood/­wikisitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlydb.tech/­en/­docs
DeveloperRackspaceSiteWhereApache Software FoundationYandex
Initial release2013201020142019
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoCommon Public Attribution License Version 1.0Open Source infoApache 2.0Open Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScala
Server operating systemsLinux
OS X
Linux
OS X
Windows
Linux
OS X
Windows
Linux
Data schemepredefined schemepredefined schemeyesFlexible Schema (defined schema, partial schema, schema free)
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.nononono
Secondary indexesnononoyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language (YQL)
APIs and other access methodsHTTP RESTHTTP RESTJDBC
ODBC
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesJava
Python
R
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresnonono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding infobased on HBaseyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandraselectable replication factor infobased on HBasenoneActive-passive shard 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 integritynononono
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.nononono
User concepts infoAccess controlnoUsers with fine-grained authorization conceptnoAccess rights defined for Yandex Cloud users

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More resources
BluefloodSiteWhereSpark SQLYDB
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