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DBMS > FatDB vs. HBase vs. TigerGraph vs. Vertica

System Properties Comparison FatDB vs. HBase vs. TigerGraph vs. Vertica

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonHBase  Xexclude from comparisonTigerGraph  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.Wide-column store based on Apache Hadoop and on concepts of BigTableA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeCloud 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
Wide column storeGraph DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score30.50
Rank#26  Overall
#2  Wide column stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitehbase.apache.orgwww.tigergraph.comwww.vertica.com
Technical documentationhbase.apache.org/­book.htmldocs.tigergraph.comvertica.com/­documentation
DeveloperFatCloudApache Software Foundation infoApache top-level project, originally developed by PowersetOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2012200820172005
Current release2.3.4, January 202112.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialcommercial 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#JavaC++C++
Server operating systemsWindowsLinux
Unix
Windows infousing Cygwin
LinuxLinux
Data schemeschema-freeschema-free, schema definition possibleyesYes, 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 dateyesoptions to bring your own types, AVROyesyes
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 indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like query language (GSQL)Full 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
Java API
RESTful HTTP API
Thrift
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC#C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infovia applicationsyes infoCoprocessors in Javayesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infovia applicationsyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-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 methodsyesyesyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)ACIDACID
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.yesnono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACRole-based access controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
FatDBHBaseTigerGraphVertica 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
FatDBHBaseTigerGraphVertica infoOpenText™ Vertica™
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