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DBMS > CrateDB vs. FileMaker vs. Google Cloud Bigtable vs. Sadas Engine

System Properties Comparison CrateDB vs. FileMaker vs. Google Cloud Bigtable vs. Sadas Engine

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonFileMaker  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionDistributed Database based on LuceneFileMaker is a cross-platform RDBMS that includes a GUI frontend.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSKey-value store
Wide column store
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.69
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#11  Vector DBMS
Score45.20
Rank#20  Overall
#14  Relational DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.00
Rank#385  Overall
#159  Relational DBMS
Websitecratedb.comwww.claris.com/­filemakercloud.google.com/­bigtablewww.sadasengine.com
Technical documentationcratedb.com/­docswww.claris.com/­resources/­documentationcloud.google.com/­bigtable/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperCrateClaris infoa subsidiary of AppleGoogleSADAS s.r.l.
Initial release2013198320152006
Current release5.8.1, August 202419.4.1, November 20218.0
License infoCommercial or Open SourceOpen Sourcecommercialcommercialcommercial infofree trial version available
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.
Implementation languageJavaC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportiOS infoclient part only
Linux
OS X
Windows
hostedAIX
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 infoA http query request can return the data in XML formatnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyes infovia pluginsnoyes
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Filemaker WebDirect
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
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
PHPC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions (Javascript)yesnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSource-replica replication, warm standby infosince Version 14Internal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
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 integritynoyesnoyes
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 strategynoAtomic single-row operations
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 infomanaged by 'Learn by Usage'
User concepts infoAccess controlrights management via user accountssimple rights management via user accounts and connection to external directory servicesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standard

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More resources
CrateDBFileMakerGoogle Cloud BigtableSadas Engine
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