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DBMS > Apache IoTDB vs. Databricks vs. OrigoDB vs. TypeDB

System Properties Comparison Apache IoTDB vs. Databricks vs. OrigoDB vs. TypeDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabricks  Xexclude from comparisonOrigoDB  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A fully ACID in-memory object graph databaseTypeDB provides developers with an expressive, customizable type system to manage their data using an award-winning query language, TypeQL, while building on a high-performance, distributed architecture.
Primary database modelTime Series DBMSDocument store
Relational DBMS
Document store
Object oriented DBMS
Graph DBMS infoThe type-theoretic data model of TypeDB subsumes the graph database model.
Object oriented DBMS infoThe data model of TypeDB comprises object-oriented features such as class inheritance and interfaces.
Relational DBMS infoThe type-theoretic data model of TypeDB subsumes the relational database model.
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#19  Object oriented DBMS
Score0.70
Rank#230  Overall
#20  Graph DBMS
#8  Object oriented DBMS
#106  Relational DBMS
Websiteiotdb.apache.orgwww.databricks.comorigodb.comtypedb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databricks.comorigodb.com/­docstypedb.com/­docs
DeveloperApache Software FoundationDatabricksRobert Friberg et alVaticle
Initial release201820132009 infounder the name LiveDB2016
Current release1.1.0, April 20232.28.3, June 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen SourceOpen Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#Java
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinux
Windows
Linux
OS X
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesUser defined using .NET types and collectionsyes
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.noyesno infocan be achieved using .NETno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagewith Databricks SQLnono
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
.NET Client API
HTTP API
LINQ
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (IDE)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Python
R
Scala
.NetAll JVM based languages
C
C++
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesyesno
Triggersyesyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioning infoclient side managed; servers are not synchronizedno
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesSource-replica replicationSynchronous replication via raft
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynodepending on modelno infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlyesRole based authorizationyes infoat REST API level; other APIs in progress
More information provided by the system vendor
Apache IoTDBDatabricksOrigoDBTypeDB infoformerly named Grakn
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
TypeDB 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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More resources
Apache IoTDBDatabricksOrigoDBTypeDB infoformerly named Grakn
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