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DBMS > Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. Qdrant vs. ToroDB

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. Qdrant vs. ToroDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonQdrant  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully managed big data interactive analytics platformA high-performance vector database with neural network or semantic-based matchingA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelKey-value store
Wide column store
Relational DBMS infocolumn orientedVector DBMSDocument store
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.16
Rank#175  Overall
#6  Vector DBMS
Websitecloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorergithub.com/­qdrant/­qdrant
qdrant.tech
github.com/­torodb/­server
Technical documentationcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerqdrant.tech/­documentation
DeveloperGoogleMicrosoftQdrant8Kdata
Initial release2015201920212016
Current releasecloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJava
Server operating systemshostedhostedDocker
Linux
macOS
Windows
All OS with a Java 7 VM
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeschema-free
Typing infopredefined data types such as float or datenoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesNumbers, Strings, Geo, Booleanyes infostring, integer, double, boolean, date, object_id
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.noyesnono
Secondary indexesnoall fields are automatically indexedyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, R
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Collection-level replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Eventual Consistency, tunable consistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory AuthenticationKey-based authenticationAccess rights for users and roles

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More resources
Google Cloud BigtableMicrosoft Azure Data ExplorerQdrantToroDB
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