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DBMS > atoti vs. CrateDB vs. FileMaker vs. Quasardb

System Properties Comparison atoti vs. CrateDB vs. FileMaker vs. Quasardb

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonCrateDB  Xexclude from comparisonFileMaker  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Distributed Database based on LuceneFileMaker is a cross-platform RDBMS that includes a GUI frontend.Distributed, high-performance timeseries database
Primary database modelObject oriented DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score48.20
Rank#20  Overall
#14  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websiteatoti.iocratedb.comwww.claris.com/­filemakerquasar.ai
Technical documentationdocs.atoti.iocratedb.com/­docswww.claris.com/­resources/­documentationdoc.quasar.ai/­master
DeveloperActiveViamCrateClaris infoa subsidiary of Applequasardb
Initial release201319832009
Current release19.4.1, November 20213.14.1, January 2024
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Sourcecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenononono
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 languageJavaJavaC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportiOS infoclient part only
Linux
OS X
Windows
BSD
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyesyes infointeger and binary
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 formatno
Secondary indexesyesyesyes infowith tags
SQL infoSupport of SQLMultidimensional Expressions (MDX)yes, but no triggers and constraints, and PostgreSQL compatibilityyes infovia pluginsSQL-like query language
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Filemaker WebDirect
JDBC
ODBC
HTTP API
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
PHP.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresPythonuser defined functions (Javascript)yesno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingnoneSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSource-replica replication, warm standby infosince Version 14Source-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate Consistency
Foreign keys infoReferential integritynoyesno
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
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoTransient mode
User concepts infoAccess controlrights management via user accountssimple rights management via user accounts and connection to external directory servicesCryptographically strong user authentication and audit trail
More information provided by the system vendor
atotiCrateDBFileMakerQuasardb
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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atotiCrateDBFileMakerQuasardb
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