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DBMS > Alibaba Cloud Table Store vs. FatDB vs. SWC-DB vs. Vertica

System Properties Comparison Alibaba Cloud Table Store vs. FatDB vs. SWC-DB vs. Vertica

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Editorial information provided by DB-Engines
NameAlibaba Cloud Table Store  Xexclude from comparisonFatDB  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  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 fully managed Wide Column Store for large quantities of semi-structured data with real-time accessA .NET NoSQL DBMS that can integrate with and extend SQL Server.A high performance, scalable Wide Column DBMSCloud 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 modelWide column storeDocument store
Key-value store
Wide column storeRelational DBMS infoColumn oriented
Secondary database modelsTime Series DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.24
Rank#310  Overall
#12  Wide column stores
Score0.01
Rank#387  Overall
#13  Wide column stores
Score11.40
Rank#43  Overall
#27  Relational DBMS
Websitewww.alibabacloud.com/­product/­table-storegithub.com/­kashirin-alex/­swc-db
www.swcdb.org
www.vertica.com
Technical documentationwww.alibabacloud.com/­help/­en/­tablestorevertica.com/­documentation
DeveloperAlibabaFatCloudAlex KashirinOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2016201220202005
Current release0.5, April 202112.0.3, January 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL V3commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnonono 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++C++
Server operating systemshostedWindowsLinuxLinux
Data schemeschema-freeschema-freeschema-freeYes, 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 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.nonono
Secondary indexesnoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like query languageFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHTTP API.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Proprietary protocol
Thrift
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJava
Python
C#C++C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infovia applicationsnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infovia applicationsnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceselectable replication factorMulti-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 methodsnoyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACID
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.nonono
User concepts infoAccess controlAccess rights based on subaccounts and tokensno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Alibaba Cloud Table StoreFatDBSWC-DB infoSuper Wide Column DatabaseVertica 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
Alibaba Cloud Table StoreFatDBSWC-DB infoSuper Wide Column DatabaseVertica infoOpenText™ Vertica™
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