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DBMS > Google Cloud Bigtable vs. Google Cloud Spanner vs. Microsoft Azure Data Explorer vs. RethinkDB vs. VictoriaMetrics

System Properties Comparison Google Cloud Bigtable vs. Google Cloud Spanner vs. Microsoft Azure Data Explorer vs. RethinkDB vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRethinkDB  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Fully managed big data interactive analytics platformDBMS for the Web with a mechanism to push updated query results to applications in realtime.A fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelKey-value store
Wide column store
Relational DBMSRelational DBMS infocolumn orientedDocument storeTime Series DBMS
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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score2.69
Rank#101  Overall
#51  Relational DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score2.58
Rank#105  Overall
#20  Document stores
Score1.23
Rank#165  Overall
#15  Time Series DBMS
Websitecloud.google.com/­bigtablecloud.google.com/­spannerazure.microsoft.com/­services/­data-explorerrethinkdb.comvictoriametrics.com
Technical documentationcloud.google.com/­bigtable/­docscloud.google.com/­spanner/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerrethinkdb.com/­docsdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperGoogleGoogleMicrosoftThe Linux Foundation infosince July 2017VictoriaMetrics
Initial release20152017201920092018
Current releasecloud service with continuous releases2.4.1, August 2020v1.91, May 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Go
Server operating systemshostedhostedhostedLinux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or datenoyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infostring, binary, float, bool, date, geometry
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.nonoyesnono
Secondary indexesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011Kusto Query Language (KQL), SQL subsetnono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Rno
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyClient-side triggers through changefeedsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding inforange based
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication with 3 replicas for regional instances.yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud DataflowSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID infoStrict serializable isolationnoAtomic single-document operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC basedyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonononono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory Authenticationyes infousers and table-level permissions

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More resources
Google Cloud BigtableGoogle Cloud SpannerMicrosoft Azure Data ExplorerRethinkDBVictoriaMetrics
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