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DBMS > Apache Druid vs. Google Cloud Datastore vs. Manticore Search vs. Microsoft Azure AI Search

System Properties Comparison Apache Druid vs. Google Cloud Datastore vs. Manticore Search vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMulti-storage database for search, including full-text search.Search-as-a-service for web and mobile app development
Primary database modelRelational DBMS
Time Series DBMS
Document storeSearch engineSearch engine
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibraryVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.22
Rank#312  Overall
#21  Search engines
Score5.59
Rank#63  Overall
#7  Search engines
Websitedruid.apache.orgcloud.google.com/­datastoremanticoresearch.comazure.microsoft.com/­en-us/­services/­search
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­datastore/­docsmanual.manticoresearch.comlearn.microsoft.com/­en-us/­azure/­search
DeveloperApache Software Foundation and contributorsGoogleManticore SoftwareMicrosoft
Initial release2012200820172015
Current release29.0.1, April 20246.0, February 2023V1
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoGPL version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsLinux
OS X
Unix
hostedFreeBSD
Linux
macOS
Windows
hosted
Data schemeyes infoschema-less columns are supportedschema-freeFixed schemayes
Typing infopredefined data types such as float or dateyesyes, details hereInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
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.nonoCan index from XMLno
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL for queryingSQL-like query language (GQL)SQL-like query languageno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresnousing Google App Engineuser defined functionsno
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication using PaxosSynchronous replication based on Galera libraryyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyes infoisolated transactions for atomic changes and binary logging for safe writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyes infousing Azure authentication

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More resources
Apache DruidGoogle Cloud DatastoreManticore SearchMicrosoft Azure AI Search
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