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DBMS > Google Cloud Bigtable vs. GridGain vs. Microsoft Azure AI Search vs. Quasardb

System Properties Comparison Google Cloud Bigtable vs. GridGain vs. Microsoft Azure AI Search vs. Quasardb

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonQuasardb  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.GridGain is an in-memory computing platform, built on Apache IgniteSearch-as-a-service for web and mobile app developmentDistributed, high-performance timeseries database
Primary database modelKey-value store
Wide column store
Columnar
Key-value store
Object oriented DBMS
Relational DBMS
Search engineTime Series DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score5.75
Rank#58  Overall
#7  Search engines
Score0.13
Rank#332  Overall
#28  Time Series DBMS
Websitecloud.google.com/­bigtablewww.gridgain.comazure.microsoft.com/­en-us/­services/­searchquasar.ai
Technical documentationcloud.google.com/­bigtable/­docswww.gridgain.com/­docs/­index.htmllearn.microsoft.com/­en-us/­azure/­searchdoc.quasar.ai/­master
DeveloperGoogleGridGain Systems, Inc.Microsoftquasardb
Initial release2015200720152009
Current releaseGridGain 8.5.1V13.14.1, January 2024
License infoCommercial or Open Sourcecommercialcommercial, open sourcecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .Net, Python, REST, SQLC++
Server operating systemshostedLinux
OS X
Solaris
Windows
z/OS
hostedBSD
Linux
OS X
Windows
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesyesyes infointeger and binary
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.noyesnono
Secondary indexesnoyesyesyes infowith tags
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLnoSQL-like query language
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
RESTful HTTP APIHTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C#
Java
JavaScript
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)nono
Triggersnoyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)yes infoImplicit feature of the cloud serviceSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)nowith Hadoop integration
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes infoTransient mode
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control
Security Hooks for custom implementations
yes infousing Azure authenticationCryptographically strong user authentication and audit trail

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More resources
Google Cloud BigtableGridGainMicrosoft Azure AI SearchQuasardb
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