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DBMS > Apache Pinot vs. Datomic vs. Google Cloud Bigtable vs. Microsoft Azure AI Search vs. Tibero

System Properties Comparison Apache Pinot vs. Datomic vs. Google Cloud Bigtable vs. Microsoft Azure AI Search vs. Tibero

Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonTibero  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Search-as-a-service for web and mobile app developmentA secure RDBMS, designed for easy portability from Oracle
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Search engineRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.52
Rank#59  Overall
#6  Search engines
Score1.59
Rank#148  Overall
#68  Relational DBMS
Websitepinot.apache.orgwww.datomic.comcloud.google.com/­bigtableazure.microsoft.com/­en-us/­services/­searchus.tmaxsoft.com/­products/­tibero
Technical documentationdocs.pinot.apache.orgdocs.datomic.comcloud.google.com/­bigtable/­docslearn.microsoft.com/­en-us/­azure/­searchtechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.html
DeveloperApache Software Foundation and contributorsCognitectGoogleMicrosoftTmaxSoft
Initial release20152012201520152003
Current release1.0.0, September 20231.0.7075, December 2023V16, April 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, ClojureC and Assembler
Server operating systemsAll OS with a Java JDK11 or higherAll OS with a Java VMhostedhostedAIX
HP-UX
Linux
Solaris
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.nononoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagenononoyes
APIs and other access methodsJDBCRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
Supported programming languagesGo
Java
Python
Clojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Python
C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnonoPersistent Stored Procedure (PSM)
TriggersBy using transaction functionsnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnone infoBut extensive use of caching in the application peersShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning infoby range, hash, list or composite
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoImplicit feature of the cloud serviceMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
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 Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnonono infoplanned for next version
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousing Azure authenticationfine grained access rights according to SQL-standard (SQL 92, SQL 99)

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More resources
Apache PinotDatomicGoogle Cloud BigtableMicrosoft Azure AI SearchTibero
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