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DBMS > Google Cloud Bigtable vs. Google Cloud Spanner vs. Microsoft Azure Synapse Analytics vs. Sequoiadb

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSequoiadb  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.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerNewSQL database with distributed OLTP and SQL
Primary database modelKey-value store
Wide column store
Relational DBMSRelational DBMSDocument store
Relational 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
Score18.98
Rank#31  Overall
#19  Relational DBMS
Score0.42
Rank#263  Overall
#41  Document stores
#121  Relational DBMS
Websitecloud.google.com/­bigtablecloud.google.com/­spannerazure.microsoft.com/­services/­synapse-analyticswww.sequoiadb.com
Technical documentationcloud.google.com/­bigtable/­docscloud.google.com/­spanner/­docsdocs.microsoft.com/­azure/­synapse-analyticswww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperGoogleGoogleMicrosoftSequoiadb Ltd.
Initial release2015201720162013
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemshostedhostedhostedLinux
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesyesyes infooid, date, timestamp, binary, regex
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 indexesnoyesyesyes
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011yesSQL-like query language
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
ADO.NET
JDBC
ODBC
proprietary protocol using JSON
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
C#
Java
PHP
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnonoTransact SQLJavaScript
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioningSharding
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.yesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno 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 operationsACID infoStrict serializable isolationACIDDocument is locked during a transaction
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.nonono
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)yessimple password-based access control

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More resources
Google Cloud BigtableGoogle Cloud SpannerMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSequoiadb
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Azure Synapse vs. Databricks: Data Platform Comparison 2024
26 March 2024, eWeek

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