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DBMS > 4D vs. CrateDB vs. Google BigQuery vs. Stardog

System Properties Comparison 4D vs. CrateDB vs. Google BigQuery vs. Stardog

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonCrateDB  Xexclude from comparisonGoogle BigQuery  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemDistributed Database based on LuceneLarge scale data warehouse service with append-only tablesEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSGraph DBMS
RDF store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitewww.4d.comcratedb.comcloud.google.com/­bigquerywww.stardog.com
Technical documentationdeveloper.4d.comcratedb.com/­docscloud.google.com/­bigquery/­docsdocs.stardog.com
Developer4D, IncCrateGoogleStardog-Union
Initial release1984201320102010
Current releasev20, April 20237.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Sourcecommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
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.
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 languageJavaJava
Server operating systemsOS X
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedLinux
macOS
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-free and OWL/RDFS-schema support
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.yesnonono infoImport/export of XML data possible
Secondary indexesyesyesnoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyes infoclose to SQL 92yes, but no triggers and constraints, and PostgreSQL compatibilityyesYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
RESTful HTTP/JSON APIGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languages4D proprietary IDE
PHP
.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
.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyesuser defined functions (Javascript)user defined functions infoin JavaScriptuser defined functions and aggregates, HTTP Server extensions in Java
Triggersyesnonoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationConfigurable replication on table/partition-levelMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyesnonoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyno infoSince BigQuery is designed for querying dataACID
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.nononoyes
User concepts infoAccess controlUsers and groupsrights management via user accountsAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users and roles
More information provided by the system vendor
4D infoformer name: 4th DimensionCrateDBGoogle BigQueryStardog
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
4D infoformer name: 4th DimensionCrateDBGoogle BigQueryStardog
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