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DBMS > Google BigQuery vs. Microsoft Azure AI Search vs. Qdrant vs. Sphinx vs. Warp 10

System Properties Comparison Google BigQuery vs. Microsoft Azure AI Search vs. Qdrant vs. Sphinx vs. Warp 10

Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonQdrant  Xexclude from comparisonSphinx  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesSearch-as-a-service for web and mobile app developmentA high-performance vector database with neural network or semantic-based matchingOpen source search engine for searching in data from different sources, e.g. relational databasesTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSSearch engineVector DBMSSearch engineTime Series DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score1.16
Rank#175  Overall
#6  Vector DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitecloud.google.com/­bigqueryazure.microsoft.com/­en-us/­services/­searchgithub.com/­qdrant/­qdrant
qdrant.tech
sphinxsearch.comwww.warp10.io
Technical documentationcloud.google.com/­bigquery/­docslearn.microsoft.com/­en-us/­azure/­searchqdrant.tech/­documentationsphinxsearch.com/­docswww.warp10.io/­content/­02_Getting_started
DeveloperGoogleMicrosoftQdrantSphinx Technologies Inc.SenX
Initial release20102015202120012015
Current releaseV13.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC++Java
Server operating systemshostedhostedDocker
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesNumbers, Strings, Geo, Booleannoyes
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.nononono
Secondary indexesnoyesyes infoKeywords, numberic ranges, geo, full-textyes infofull-text index on all search fieldsno
SQL infoSupport of SQLyesnonoSQL-like query language (SphinxQL)no
APIs and other access methodsRESTful HTTP/JSON APIRESTful HTTP APIgRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Proprietary protocolHTTP API
Jupyter
WebSocket
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C#
Java
JavaScript
Python
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptnonoyes infoWarpScript
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceCollection-level replicationnoneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency, tunable consistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)yes infousing Azure authenticationKey-based authenticationnoMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Google BigQueryMicrosoft Azure AI SearchQdrantSphinxWarp 10
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