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DBMS > 4D vs. CrateDB vs. Microsoft Azure AI Search vs. Splice Machine

System Properties Comparison 4D vs. CrateDB vs. Microsoft Azure AI Search vs. Splice Machine

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonCrateDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemDistributed Database based on LuceneSearch-as-a-service for web and mobile app developmentOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Search engineRelational DBMS
Secondary database modelsRelational DBMSVector 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
Score5.59
Rank#63  Overall
#7  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.4d.comcratedb.comazure.microsoft.com/­en-us/­services/­searchsplicemachine.com
Technical documentationdeveloper.4d.comcratedb.com/­docslearn.microsoft.com/­en-us/­azure/­searchsplicemachine.com/­how-it-works
Developer4D, IncCrateMicrosoftSplice Machine
Initial release1984201320152014
Current releasev20, April 2023V13.1, March 2021
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoAGPL 3.0, commercial license available
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
OS X
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
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.yesnono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infoclose to SQL 92yes, but no triggers and constraints, and PostgreSQL compatibilitynoyes
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 APIJDBC
Native Spark Datasource
ODBC
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
C#
Java
JavaScript
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functions (Javascript)noyes infoJava
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationConfigurable replication on table/partition-levelyes infoImplicit feature of the cloud serviceMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
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 strategynoACID
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.nononoyes
User concepts infoAccess controlUsers and groupsrights management via user accountsyes infousing Azure authenticationAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
4D infoformer name: 4th DimensionCrateDBMicrosoft Azure AI SearchSplice Machine
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 DimensionCrateDBMicrosoft Azure AI SearchSplice Machine
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