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DBMS > GreptimeDB vs. Microsoft Azure AI Search vs. Oracle Berkeley DB vs. Sphinx

System Properties Comparison GreptimeDB vs. Microsoft Azure AI Search vs. Oracle Berkeley DB vs. Sphinx

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Editorial information provided by DB-Engines
NameGreptimeDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAn open source Time Series DBMS built for increased scalability, high performance and efficiencySearch-as-a-service for web and mobile app developmentWidely used in-process key-value storeOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSSearch engineKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Search engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.12
Rank#351  Overall
#34  Time Series DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitegreptime.comazure.microsoft.com/­en-us/­services/­searchwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsphinxsearch.com
Technical documentationdocs.greptime.comlearn.microsoft.com/­en-us/­azure/­searchdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsphinxsearch.com/­docs
DeveloperGreptime Inc.MicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleSphinx Technologies Inc.
Initial release2022201519942001
Current releaseV118.1.40, May 20203.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infocommercial license availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemsAndroid
Docker
FreeBSD
Linux
macOS
Windows
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-free, schema definition possibleyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnono
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.nonoyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesnoyes infoSQL interfaced based on SQLite is availableSQL-like query language (SphinxQL)
APIs and other access methodsgRPC
HTTP API
JDBC
RESTful HTTP APIProprietary protocol
Supported programming languagesC++
Erlang
Go
Java
JavaScript
C#
Java
JavaScript
Python
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresPythonnonono
Triggersnoyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlSimple rights management via user accountsyes infousing Azure authenticationnono
More information provided by the system vendor
GreptimeDBMicrosoft Azure AI SearchOracle Berkeley DBSphinx
Specific characteristicsGreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more
Competitive advantages- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more
Typical application scenariosFor IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more
Key customersGreptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more
Market metricsGreptimeDB has garnered global recognition by topping GitHub trends following its...
» more
Licensing and pricing modelsGreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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GreptimeDBMicrosoft Azure AI SearchOracle Berkeley DBSphinx
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