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DBMS > Google Cloud Bigtable vs. Graph Engine vs. Quasardb vs. Sadas Engine

System Properties Comparison Google Cloud Bigtable vs. Graph Engine vs. Quasardb vs. Sadas Engine

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonQuasardb  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineDistributed, high-performance timeseries databaseSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelKey-value store
Wide column store
Graph DBMS
Key-value 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
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websitecloud.google.com/­bigtablewww.graphengine.ioquasar.aiwww.sadasengine.com
Technical documentationcloud.google.com/­bigtable/­docswww.graphengine.io/­docs/­manualdoc.quasar.ai/­masterwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperGoogleMicrosoftquasardbSADAS s.r.l.
Initial release2015201020092006
Current release3.14.1, January 20248.0
License infoCommercial or Open SourcecommercialOpen Source infoMIT Licensecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensescommercial infofree trial version available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CC++C++
Server operating systemshosted.NETBSD
Linux
OS X
Windows
AIX
Linux
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesyes 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.nononono
Secondary indexesnoyes infowith tagsyes
SQL infoSupport of SQLnonoSQL-like query languageyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIHTTP APIJDBC
ODBC
Proprietary protocol
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
F#
Visual Basic
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresnoyesnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infoconsistent hashinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyeswith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 dataAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoTransient modeyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Cryptographically strong user authentication and audit trailAccess rights for users, groups and roles according to SQL-standard

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More resources
Google Cloud BigtableGraph Engine infoformer name: TrinityQuasardbSadas Engine
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