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

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

Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonTibero  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Search-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
Document storeSearch 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
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.60
Rank#244  Overall
#38  Document stores
Score5.52
Rank#59  Overall
#6  Search engines
Score1.59
Rank#148  Overall
#68  Relational DBMS
Websitepinot.apache.orgcloud.google.com/­bigtablewww.harperdb.ioazure.microsoft.com/­en-us/­services/­searchus.tmaxsoft.com/­products/­tibero
Technical documentationdocs.pinot.apache.orgcloud.google.com/­bigtable/­docsdocs.harperdb.io/­docslearn.microsoft.com/­en-us/­azure/­searchtechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.html
DeveloperApache Software Foundation and contributorsGoogleHarperDBMicrosoftTmaxSoft
Initial release20152015201720152003
Current release1.0.0, September 20233.1, August 2021V16, April 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree community edition availablecommercialcommercial
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 languageJavaNode.jsC and Assembler
Server operating systemsAll OS with a Java JDK11 or higherhostedLinux
OS X
hostedAIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freedynamic schemayesyes
Typing infopredefined data types such as float or dateyesnoyes infoJSON data typesyesyes
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 indexesnoyesyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like data manipulation statementsnoyes
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
RESTful HTTP APIJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
Supported programming languagesGo
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C#
Java
JavaScript
Python
C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1noPersistent Stored Procedure (PSM)
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingA table resides as a whole on one (or more) nodes in a clusterSharding infoImplicit feature of the cloud servicehorizontal partitioning infoby range, hash, list or composite
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be definedyes infoImplicit feature of the cloud serviceMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
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 integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsAtomic execution of specific operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono infoplanned for next version
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesyes infousing Azure authenticationfine grained access rights according to SQL-standard (SQL 92, SQL 99)

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More resources
Apache PinotGoogle Cloud BigtableHarperDBMicrosoft Azure AI SearchTibero
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