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DBMS > FatDB vs. Vertica vs. Yaacomo

System Properties Comparison FatDB vs. Vertica vs. Yaacomo

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparisonYaacomo  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.Cloud or on-premises 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.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Key-value store
Relational DBMS infoColumn orientedRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score19.29
Rank#38  Overall
#24  Relational DBMS
Score0.00
Rank#354  Overall
#152  Relational DBMS
Websitewww.vertica.comyaacomo.com
Technical documentationvertica.com/­documentation
DeveloperFatCloudMicro Focus infoprior to that Hewlett PackardQ2WEB GmbH
Initial release201220052009
Current release11.1, February 2022
License infoCommercial or Open Sourcecommercialcommercial infoLimited community edition freecommercial
Cloud-based only infoOnly available as a cloud servicenono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Vertica Accelerator’s high-performance analytics and machine learning with SQL or Python is available as a managed service.
Implementation languageC#C++
Server operating systemsWindowsLinuxAndroid
Linux
Windows
Data schemeschema-freeyes, but unstructured data can be stored in specific Flex-Tablesyes
Typing infopredefined data types such as float or dateyesyes: BINARY, BOOLEAN, CHAR, VARCHAR, LONG VARCHAR, DATE, TIME, TIMESTAMP, INTERVAL, INTERVAL DAY TO SECOND, INTERVAL YEAR TO MONTH, DOUBLE PRECISION, FLOAT, INTEGER, BIGINT, SMALLINT,NUMERIC, DECIMAL, NUMBER, MONEY,GEOMETRYyes
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 indexesyesNo Indexes Requiredyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.yes
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
JDBC
ODBC
Supported programming languagesC#C#
C++
Java
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infovia applicationsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infovia applicationsyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning, hierarchical partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
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.noyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashfine grained access rights according to SQL-standard
More information provided by the system vendor
FatDBVertica infoVertica Analytics PlatformYaacomo
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy on-premises,...
» more
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,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
FatDBVertica infoVertica Analytics PlatformYaacomo
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