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DBMS > FatDB vs. Google Cloud Bigtable vs. Quasardb vs. TimesTen

System Properties Comparison FatDB vs. Google Cloud Bigtable vs. Quasardb vs. TimesTen

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonQuasardb  Xexclude from comparisonTimesTen  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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Distributed, high-performance timeseries databaseIn-Memory RDBMS compatible to Oracle
Primary database modelDocument store
Key-value store
Key-value store
Wide column store
Time Series DBMSRelational 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
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitecloud.google.com/­bigtablequasar.aiwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationcloud.google.com/­bigtable/­docsdoc.quasar.ai/­masterdocs.oracle.com/­database/­timesten-18.1
DeveloperFatCloudGooglequasardbOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2012201520091998
Current release3.14.1, January 202411 Release 2 (11.2.2.8.0)
License infoCommercial or Open Sourcecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensescommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C++
Server operating systemsWindowshostedBSD
Linux
OS X
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes infointeger and binaryyes
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 indexesyesnoyes infowith tagsyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like query languageyes
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)
HTTP APIJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC#C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyes infovia applicationsnonoPL/SQL
Triggersyes infovia applicationsnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoconsistent hashingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication with selectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyeswith Hadoop integrationno
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 or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeyes
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)Cryptographically strong user authentication and audit trailfine grained access rights according to SQL-standard

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More resources
FatDBGoogle Cloud BigtableQuasardbTimesTen
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