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DBMS > FeatureBase vs. Spark SQL vs. Teradata Aster

System Properties Comparison FeatureBase vs. Spark SQL vs. Teradata Aster

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Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Spark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#309  Overall
#139  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.featurebase.comspark.apache.org/­sql
Technical documentationdocs.featurebase.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMolecula and Pilosa Open Source ContributorsApache Software FoundationTeradata
Initial release201720142005
Current release2022, May 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen 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 languageGoScala
Server operating systemsLinux
macOS
Linux
OS X
Windows
Linux
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyes
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.nonoyes infoin Aster File Store
Secondary indexesnonoyes
SQL infoSupport of SQLSQL queriesSQL-like DML and DDL statementsyes
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesJava
Python
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoR packages
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes, using Linux fsyncyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnofine grained access rights according to SQL-standard

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More resources
FeatureBaseSpark SQLTeradata Aster
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