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DBMS > Databend vs. Google Cloud Bigtable vs. Linter vs. Microsoft Azure AI Search vs. Tibero

System Properties Comparison Databend vs. Google Cloud Bigtable vs. Linter vs. Microsoft Azure AI Search vs. Tibero

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonTibero  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.RDBMS for high security requirementsSearch-as-a-service for web and mobile app developmentA secure RDBMS, designed for easy portability from Oracle
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.12
Rank#350  Overall
#152  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score1.59
Rank#148  Overall
#68  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
cloud.google.com/­bigtablelinter.ruazure.microsoft.com/­en-us/­services/­searchus.tmaxsoft.com/­products/­tibero
Technical documentationdocs.databend.comcloud.google.com/­bigtable/­docslearn.microsoft.com/­en-us/­azure/­searchtechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.html
DeveloperDatabend LabsGooglerelex.ruMicrosoftTmaxSoft
Initial release20212015199020152003
Current release1.0.59, April 2023V16, April 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC and C++C and Assembler
Server operating systemshosted
Linux
macOS
hostedAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hostedAIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nonononoyes
Secondary indexesnonoyesyesyes
SQL infoSupport of SQLyesnoyesnoyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
RESTful HTTP APIJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C#
Java
JavaScript
Python
C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresnonoyes infoproprietary syntax with the possibility to convert from PL/SQLnoPersistent Stored Procedure (PSM)
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding infoImplicit feature of the cloud servicehorizontal partitioning infoby range, hash, list or composite
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes infoImplicit feature of the cloud serviceMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesAtomic single-row operationsACIDnoACID
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.nonono infoplanned for next version
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardyes infousing Azure authenticationfine grained access rights according to SQL-standard (SQL 92, SQL 99)

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More resources
DatabendGoogle Cloud BigtableLinterMicrosoft Azure AI SearchTibero
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