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DBMS > Spark SQL vs. SQream DB vs. TimesTen vs. Vertica

System Properties Comparison Spark SQL vs. SQream DB vs. TimesTen vs. Vertica

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonSQream DB  Xexclude from comparisonTimesTen  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloadsIn-Memory RDBMS compatible to OracleCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitespark.apache.org/­sqlsqream.comwww.oracle.com/­database/­technologies/­related/­timesten.htmlwww.vertica.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.comdocs.oracle.com/­database/­timesten-18.1vertica.com/­documentation
DeveloperApache Software FoundationSQream TechnologiesOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2014201719982005
Current release3.5.0 ( 2.13), September 20232022.1.6, December 202211 Release 2 (11.2.2.8.0)12.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++, CUDA, Haskell, Java, ScalaC++
Server operating systemsLinux
OS X
Windows
LinuxAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
Data schemeyesyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyes
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 indexesnonoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
.Net
JDBC
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJava
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
C
C++
Java
PL/SQL
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnouser defined functions in PythonPL/SQLyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Corehorizontal and vertical partitioningnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replication
Source-replica replication
Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby means of logfiles and checkpointsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Spark SQLSQream DBTimesTenVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Spark SQLSQream DBTimesTenVertica infoOpenText™ Vertica™
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