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DBMS > Spark SQL vs. Transbase vs. Vertica

System Properties Comparison Spark SQL vs. Transbase vs. Vertica

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMSColumnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score21.39
Rank#34  Overall
#20  Relational DBMS
Score0.26
Rank#279  Overall
#129  Relational DBMS
Score21.10
Rank#35  Overall
#21  Relational DBMS
Websitespark.apache.org/­sqlwww.transaction.de/­en/­solutions/­transbase-resource-optimized-high-performance-databasewww.vertica.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­transbase-insidewww.vertica.com/­docs/­10.0.x/­HTML/­Content/­Home.htm
DeveloperApache Software FoundationTransaction Software GmbHVertica / Micro Focus infoprior to that Hewlett Packard
Initial release201419872005
Current release3.1.1, March 2021Transbase 8.4, September 2020Vertica 10.0 Software, May 2020
Vertica for SQL on Hadoop 10.0 Software, May 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infofree development licensecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoAvailable on all major clouds - Amazon AWS, Microsoft Azure and Google Cloud Platform
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC and C++
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Linux
Data schemeyesyesyes infoUnstructured data can be stored in specific Flex-Tables
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
Secondary indexesnoyesno infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
ADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languagesJava
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresnoyesyes
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACID
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.nono
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 SQLTransbaseVertica infoVertica Analytics Platform
Specific characteristicsColumnar storage, MPP, Hybrid storage model, Aggressive data compression, High availability,...
» more
Competitive advantagesPerformance at exabyte scale, Deploy anywhere, Open source innovation, Analysis in...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are available
» more

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More resources
Spark SQLTransbaseVertica infoVertica Analytics Platform
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