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

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

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
DescriptionDistributed Database based on LuceneGoogle'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 Server
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value store
Wide column store
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#229  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score22.71
Rank#30  Overall
#18  Relational DBMS
Websitecratedb.comcloud.google.com/­bigtableazure.microsoft.com/­services/­synapse-analytics
Technical documentationcratedb.com/­docscloud.google.com/­bigtable/­docsdocs.microsoft.com/­azure/­synapse-analytics
DeveloperCrateGoogleMicrosoft
Initial release201320152016
License infoCommercial or Open SourceOpen Sourcecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedhosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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 indexesyesnoyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoyes
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
Java
PHP
Server-side scripts infoStored proceduresuser defined functions (Javascript)noTransact SQL
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelInternal replication in Colossus, and regional replication between two clusters in different zonesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyAtomic single-row operationsACID
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 controlrights management via user accountsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes
More information provided by the system vendor
CrateDBGoogle Cloud BigtableMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
CrateDBGoogle Cloud BigtableMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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