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DBMS > 4D vs. Apache IoTDB vs. Solr vs. TypeDB

System Properties Comparison 4D vs. Apache IoTDB vs. Solr vs. TypeDB

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonApache IoTDB  Xexclude from comparisonSolr  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA widely used distributed, scalable search engine based on Apache LuceneTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelRelational DBMSTime Series DBMSSearch engineGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.47
Rank#110  Overall
#54  Relational DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.70
Rank#230  Overall
#20  Graph DBMS
#106  Relational DBMS
Websitewww.4d.comiotdb.apache.orgsolr.apache.orgtypedb.com
Technical documentationdeveloper.4d.comiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlsolr.apache.org/­resources.htmltypedb.com/­docs
Developer4D, IncApache Software FoundationApache Software FoundationVaticle
Initial release1984201820062016
Current releasev20, April 20231.1.0, April 20239.6.1, May 20242.26.3, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsOS X
Windows
All OS with a Java VM (>= 1.8)All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyes
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.yesnoyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyes infoclose to SQL 92SQL-like query languageSolr Parallel SQL Interfaceno
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
JDBC
Native API
Java API
RESTful HTTP/JSON API
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languages4D proprietary IDE
PHP
C
C#
C++
Go
Java
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyesyesJava pluginsno
Triggersyesyesyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesMulti-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparkspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes infoby using Apache Kafka and Apache Zookeeper
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingACID
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.noyesyesno
User concepts infoAccess controlUsers and groupsyesyesyes infoat REST API level; other APIs in progress
More information provided by the system vendor
4D infoformer name: 4th DimensionApache IoTDBSolrTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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4D infoformer name: 4th DimensionApache IoTDBSolrTypeDB infoformerly named Grakn
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