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DBMS > Amazon SimpleDB vs. CrateDB vs. Databricks vs. FatDB

System Properties Comparison Amazon SimpleDB vs. CrateDB vs. Databricks vs. FatDB

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonCrateDB  Xexclude from comparisonDatabricks  Xexclude from comparisonFatDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreDistributed Database based on LuceneThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A .NET NoSQL DBMS that can integrate with and extend SQL Server.
Primary database modelKey-value storeDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Document store
Relational DBMS
Document store
Key-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Websiteaws.amazon.com/­simpledbcratedb.comwww.databricks.com
Technical documentationdocs.aws.amazon.com/­simpledbcratedb.com/­docsdocs.databricks.com
DeveloperAmazonCrateDatabricksFatCloud
Initial release2007201320132012
License infoCommercial or Open SourcecommercialOpen Sourcecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
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 systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedWindows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)Flexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or datenoyesyes
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.noyes
Secondary indexesyes infoAll columns are indexed automaticallyyesyesyes
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilitywith Databricks SQLno infoVia inetgration in SQL Server
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
.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
Python
R
Scala
C#
Server-side scripts infoStored proceduresnouser defined functions (Javascript)user defined functions and aggregatesyes infovia applications
Triggersnonoyes infovia applications
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesConfigurable replication on table/partition-levelyesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDno
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.nono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)rights management via user accountsno infoCan implement custom security layer via applications
More information provided by the system vendor
Amazon SimpleDBCrateDBDatabricksFatDB
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
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Supported database models : In addition to the Document store and Relational DBMS...
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Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
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Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
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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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Amazon SimpleDBCrateDBDatabricksFatDB
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