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DBMS > FatDB vs. Google Cloud Bigtable vs. Hypertable vs. Linter vs. Microsoft Azure Synapse Analytics

System Properties Comparison FatDB vs. Google Cloud Bigtable vs. Hypertable vs. Linter vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHypertable  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.An open source BigTable implementation based on distributed file systems such as HadoopRDBMS for high security requirementsElastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelDocument store
Key-value store
Key-value store
Wide column store
Wide column storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websitecloud.google.com/­bigtablelinter.ruazure.microsoft.com/­services/­synapse-analytics
Technical documentationcloud.google.com/­bigtable/­docsdocs.microsoft.com/­azure/­synapse-analytics
DeveloperFatCloudGoogleHypertable Inc.relex.ruMicrosoft
Initial release20122015200919902016
Current release0.9.8.11, March 2016
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGNU version 3. Commercial license availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C++C and C++C++
Server operating systemsWindowshostedLinux
OS X
Windows infoan inofficial Windows port is available
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hosted
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnonoyesyes
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 indexesyesnorestricted infoonly exact value or prefix value scansyesyes
SQL infoSupport of SQLno infoVia inetgration in SQL Servernonoyesyes
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
C++ API
Thrift
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
ADO.NET
JDBC
ODBC
Supported programming languagesC#C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C#
Java
PHP
Server-side scripts infoStored proceduresyes infovia applicationsnonoyes infoproprietary syntax with the possibility to convert from PL/SQLTransact SQL
Triggersyes infovia applicationsnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor on file system levelSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyesnono
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnoACIDACID
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.no
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)nofine grained access rights according to SQL-standardyes

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More resources
FatDBGoogle Cloud BigtableHypertableLinterMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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