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DBMS > Google Cloud Bigtable vs. Microsoft Azure Synapse Analytics vs. VictoriaMetrics

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure Synapse Analytics vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  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.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelKey-value store
Wide column store
Relational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score22.71
Rank#30  Overall
#18  Relational DBMS
Score1.42
Rank#161  Overall
#14  Time Series DBMS
Websitecloud.google.com/­bigtableazure.microsoft.com/­services/­synapse-analyticsvictoriametrics.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.microsoft.com/­azure/­synapse-analyticsdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperGoogleMicrosoftVictoriaMetrics
Initial release201520162018
Current releasev1.91, May 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Go
Server operating systemshostedhostedFreeBSD
Linux
macOS
OpenBSD
Data schemeschema-freeyes
Typing infopredefined data types such as float or datenoyes
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.nonono
Secondary indexesnoyes
SQL infoSupport of SQLnoyesno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
Java
PHP
Server-side scripts infoStored proceduresnoTransact SQLno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyesSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
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
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes

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More resources
Google Cloud BigtableMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseVictoriaMetrics
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