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DBMS > CockroachDB vs. FatDB vs. Google Cloud Datastore vs. Microsoft Azure Table Storage vs. Yaacomo

System Properties Comparison CockroachDB vs. FatDB vs. Google Cloud Datastore vs. Microsoft Azure Table Storage vs. Yaacomo

Editorial information provided by DB-Engines
NameCockroachDB  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonYaacomo  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Wide Column Store for rapid development using massive semi-structured datasetsOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSDocument store
Key-value store
Document storeWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitewww.cockroachlabs.comcloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­storage/­tablesyaacomo.com
Technical documentationwww.cockroachlabs.com/­docscloud.google.com/­datastore/­docs
DeveloperCockroach LabsFatCloudGoogleMicrosoftQ2WEB GmbH
Initial release20152012200820122009
Current release23.1.1, May 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0, commercial license availablecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC#
Server operating systemsLinux
macOS
Windows
WindowshostedhostedAndroid
Linux
Windows
Data schemedynamic schemaschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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 indexesyesyesyesnoyes
SQL infoSupport of SQLyes, wire compatible with PostgreSQLno infoVia inetgration in SQL ServerSQL-like query language (GQL)noyes
APIs and other access methodsJDBC.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIJDBC
ODBC
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infovia applicationsusing Google App Engineno
Triggersnoyes infovia applicationsCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTselectable replication factorMulti-source replication using Paxosyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nononoyes
User concepts infoAccess controlRole-based access controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standard

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More resources
CockroachDBFatDBGoogle Cloud DatastoreMicrosoft Azure Table StorageYaacomo
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