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DBMS > FatDB vs. IBM Db2 vs. Spark SQL vs. Vertica

System Properties Comparison FatDB vs. IBM Db2 vs. Spark SQL vs. Vertica

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonSpark SQL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Common in IBM host environments, 2 different versions for host and Windows/LinuxSpark SQL is a component on top of 'Spark Core' for structured data processingCloud 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 modelDocument store
Key-value store
Relational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score128.46
Rank#8  Overall
#5  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.ibm.com/­products/­db2spark.apache.org/­sqlwww.vertica.com
Technical documentationwww.ibm.com/­docs/­en/­db2spark.apache.org/­docs/­latest/­sql-programming-guide.htmlvertica.com/­documentation
DeveloperFatCloudIBMApache Software FoundationOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20121983 infohost version20142005
Current release12.1, October 20163.5.0 ( 2.13), September 202312.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercial infofree version is availableOpen Source infoApache 2.0commercial 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 languageC#C and C++ScalaC++
Server operating systemsWindowsAIX
HP-UX
Linux
Solaris
Windows
z/OS
Linux
OS X
Windows
Linux
Data schemeschema-freeyesyesYes, 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 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.nono
Secondary indexesyesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesSQL-like DML and DDL statementsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC#C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
Java
Python
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infovia applicationsyesnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infovia applicationsyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoonly with Windows/Unix/Linux Versionyes, utilizing Spark Corehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infowith separate tools (MQ, InfoSphere)noneMulti-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 methodsyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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.nono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
FatDBIBM Db2 infoformerly named DB2 or IBM Database 2Spark SQLVertica 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
FatDBIBM Db2 infoformerly named DB2 or IBM Database 2Spark SQLVertica infoOpenText™ Vertica™
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