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DBMS > BigObject vs. Blueflood vs. CrateDB vs. RDFox

System Properties Comparison BigObject vs. Blueflood vs. CrateDB vs. RDFox

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonBlueflood  Xexclude from comparisonCrateDB  Xexclude from comparisonRDFox  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesScalable TimeSeries DBMS based on CassandraDistributed Database based on LuceneHigh performance knowledge graph and semantic reasoning engine
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedTime Series DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Graph DBMS
RDF store
Secondary database modelsRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.06
Rank#353  Overall
#34  Time Series DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Websitebigobject.ioblueflood.iocratedb.comwww.oxfordsemantic.tech
Technical documentationdocs.bigobject.iogithub.com/­rax-maas/­blueflood/­wikicratedb.com/­docsdocs.oxfordsemantic.tech
DeveloperBigObject, Inc.RackspaceCrateOxford Semantic Technologies
Initial release2015201320132017
Current release6.0, Septermber 2022
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoApache 2.0Open Sourcecommercial
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 systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
macOS
Windows
Data schemeyespredefined schemeFlexible Schema (defined schema, partial schema, schema free)yes infoRDF schemas
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes, but no triggers and constraints, and PostgreSQL compatibilityno
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
HTTP RESTADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
RESTful HTTP API
SPARQL 1.1
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
Java
Server-side scripts infoStored proceduresLuanouser defined functions (Javascript)
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor infobased on CassandraConfigurable replication on table/partition-levelreplication via a shared file system
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Read-after-write consistency on record level
Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyes
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.yesnonoyes
User concepts infoAccess controlnonorights management via user accountsRoles, resources, and access types
More information provided by the system vendor
BigObjectBluefloodCrateDBRDFox
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
BigObjectBluefloodCrateDBRDFox
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