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DBMS > 4D vs. AnzoGraph DB vs. CrateDB vs. ITTIA

System Properties Comparison 4D vs. AnzoGraph DB vs. CrateDB vs. ITTIA

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonAnzoGraph DB  Xexclude from comparisonCrateDB  Xexclude from comparisonITTIA  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationDistributed Database based on LuceneEdge Time Series DBMS with Real-Time Stream Processing
Primary database modelRelational DBMSGraph DBMS
RDF store
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Time Series DBMS
Secondary database modelsRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.47
Rank#110  Overall
#54  Relational DBMS
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#9  Vector DBMS
Score0.44
Rank#267  Overall
#23  Time Series DBMS
Websitewww.4d.comcambridgesemantics.com/­anzographcratedb.comwww.ittia.com
Technical documentationdeveloper.4d.comdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmcratedb.com/­docs
Developer4D, IncCambridge SemanticsCrateITTIA L.L.C.
Initial release1984201820132007
Current releasev20, April 20232.3, January 20218.7
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availableOpen 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 languageJavaC and C++
Server operating systemsOS X
Windows
LinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
Windows
Data schemeyesSchema-free and OWL/RDFS-schema supportFlexible Schema (defined schema, partial schema, schema free)Fixed schema
Typing infopredefined data types such as float or dateyesyesFloat/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval
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
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes infoclose to SQL 92SPARQL and SPARQL* as primary query language. Cypher preview.yes, but no triggers and constraints, and PostgreSQL compatibilityyes
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
WebSocket
Supported programming languages4D proprietary IDE
PHP
C++
Java
Python
.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
C++
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesuser defined functions (Javascript)yes
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication in MPP-ClusterConfigurable replication on table/partition-levelyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoKerberos/HDFS data loadingnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in MPP-ClusterEventual Consistency
Read-after-write consistency on record level
Foreign keys infoReferential integrityyesno infonot needed in graphsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.noyesnoyes
User concepts infoAccess controlUsers and groupsAccess rights for users and rolesrights management via user accountsDatabase file passwords
More information provided by the system vendor
4D infoformer name: 4th DimensionAnzoGraph DBCrateDBITTIA
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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4D infoformer name: 4th DimensionAnzoGraph DBCrateDBITTIA
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