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DBMS > BigObject vs. CrateDB vs. RDF4J vs. Spark SQL

System Properties Comparison BigObject vs. CrateDB vs. RDF4J vs. Spark SQL

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonCrateDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesDistributed Database based on LuceneRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
RDF storeRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitebigobject.iocratedb.comrdf4j.orgspark.apache.org/­sql
Technical documentationdocs.bigobject.iocratedb.com/­docsrdf4j.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBigObject, Inc.CrateSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software Foundation
Initial release2015201320042014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen SourceOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 2.0
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 languageJavaJavaScala
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yes infoRDF Schemasyes
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 indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyes, but no triggers and constraints, and PostgreSQL compatibilitynoSQL-like DML and DDL statements
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
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
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresLuauser defined functions (Javascript)yesno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneConfigurable replication on table/partition-levelnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Read-after-write consistency on record level
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnorights management via user accountsnono
More information provided by the system vendor
BigObjectCrateDBRDF4J infoformerly known as SesameSpark SQL
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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BigObjectCrateDBRDF4J infoformerly known as SesameSpark SQL
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