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DBMS > FatDB vs. Firebolt vs. Google Cloud Bigtable vs. Microsoft Azure Table Storage vs. Yaacomo

System Properties Comparison FatDB vs. Firebolt vs. Google Cloud Bigtable vs. Microsoft Azure Table Storage vs. Yaacomo

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonFirebolt  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Table Storage  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.Highly scalable cloud data warehouse and analytics product infoForked from ClickhouseGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A Wide Column Store for rapid development using massive semi-structured datasetsOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Key-value store
Relational DBMSKey-value store
Wide column store
Wide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.49
Rank#148  Overall
#68  Relational DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score3.55
Rank#80  Overall
#6  Wide column stores
Websitewww.firebolt.iocloud.google.com/­bigtableazure.microsoft.com/­en-us/­services/­storage/­tablesyaacomo.com
Technical documentationdocs.firebolt.iocloud.google.com/­bigtable/­docs
DeveloperFatCloudFirebolt Analytics Inc.GoogleMicrosoftQ2WEB GmbH
Initial release20122020201520122009
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#
Server operating systemsWindowshostedhostedhostedAndroid
Linux
Windows
Data schemeschema-freeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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 indexesyesyesnonoyes
SQL infoSupport of SQLno infoVia inetgration in SQL Serveryesnonoyes
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
.Net
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIJDBC
ODBC
Supported programming languagesC#Go
JavaScript (Node.js)
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infovia applicationsnonono
Triggersyes infovia applicationsnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factordepending on storage layerInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsoptimistic lockingACID
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.nonoyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standard

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More resources
FatDBFireboltGoogle Cloud BigtableMicrosoft Azure Table StorageYaacomo
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