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DBMS > CrateDB vs. FatDB vs. Google Cloud Datastore vs. Warp 10

System Properties Comparison CrateDB vs. FatDB vs. Google Cloud Datastore vs. Warp 10

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonWarp 10  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionDistributed Database based on LuceneA .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Document store
Key-value store
Document storeTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitecratedb.comcloud.google.com/­datastorewww.warp10.io
Technical documentationcratedb.com/­docscloud.google.com/­datastore/­docswww.warp10.io/­content/­02_Getting_started
DeveloperCrateFatCloudGoogleSenX
Initial release2013201220082015
License infoCommercial or Open SourceOpen SourcecommercialcommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
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#Java
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportWindowshostedLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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 indexesyesyesyesno
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityno infoVia inetgration in SQL ServerSQL-like query language (GQL)no
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Jupyter
WebSocket
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#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions (Javascript)yes infovia applicationsusing Google App Engineyes infoWarpScript
Triggersnoyes infovia applicationsCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelselectable replication factorMulti-source replication using Paxosselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual 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 Consistency infobased on HBase
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
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 strategynoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
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.nonoyes
User concepts infoAccess controlrights management via user accountsno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Mandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
CrateDBFatDBGoogle Cloud DatastoreWarp 10
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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More resources
CrateDBFatDBGoogle Cloud DatastoreWarp 10
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