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DBMS > FatDB vs. Microsoft Azure Table Storage vs. ObjectBox vs. Vertica vs. Yaacomo

System Properties Comparison FatDB vs. Microsoft Azure Table Storage vs. ObjectBox vs. Vertica vs. Yaacomo

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonObjectBox  Xexclude from comparisonVertica infoOpenText™ Vertica™  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.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.A Wide Column Store for rapid development using massive semi-structured datasetsLightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectorsCloud 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.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Key-value store
Wide column storeObject oriented DBMS
Vector DBMS
Relational DBMS infoColumn orientedRelational DBMS
Secondary database modelsTime Series DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.04
Rank#77  Overall
#6  Wide column stores
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
#7  Vector DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablesgithub.com/­objectbox
objectbox.io
www.vertica.comyaacomo.com
Technical documentationdocs.objectbox.iovertica.com/­documentation
DeveloperFatCloudMicrosoftObjectBox LimitedOpenText infopreviously Micro Focus and Hewlett PackardQ2WEB GmbH
Initial release20122012201720052009
Current release4.0 (May 2024)12.0.3, January 2023
License infoCommercial or Open SourcecommercialcommercialBindings are released under Apache 2.0 infoApache License 2.0commercial infoLimited community edition freecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C and C++C++
Server operating systemsWindowshostedAndroid
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows
LinuxAndroid
Linux
Windows
Data schemeschema-freeschema-freeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes
Typing infopredefined data types such as float or dateyesyesyes, plus "flex" map-like typesyesyes
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.nononono
Secondary indexesyesnoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.yes
SQL infoSupport of SQLno infoVia inetgration in SQL ServernonoFull 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
RESTful HTTP APIProprietary native APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
JDBC
ODBC
Supported programming languagesC#.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infovia applicationsnonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infovia applicationsnonoyes, called Custom Alertsyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenonehorizontal partitioning, hierarchical partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Data sync between devices allowing occasional connected databases to work completely offlineMulti-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 methodsyesnonono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights based on private key authentication or shared access signaturesyesfine 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
FatDBMicrosoft Azure Table StorageObjectBoxVertica infoOpenText™ Vertica™Yaacomo
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» 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...
» more
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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