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DBMS > Apache IoTDB vs. Databricks vs. H2

System Properties Comparison Apache IoTDB vs. Databricks vs. H2

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabricks  Xexclude from comparisonH2  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.Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.
Primary database modelTime Series DBMSDocument store
Relational DBMS
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.13
Rank#199  Overall
#16  Time Series DBMS
Score76.91
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score8.50
Rank#51  Overall
#32  Relational DBMS
Websiteiotdb.apache.orgwww.databricks.comwww.h2database.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databricks.comwww.h2database.com/­html/­main.html
DeveloperApache Software FoundationDatabricksThomas Mueller
Initial release201820132005
Current release1.1.0, April 20232.2.220, July 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)hostedAll OS with a Java VM
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyes
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
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query languagewith Databricks SQLyes
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Python
R
Scala
Java
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesJava Stored Procedures and User-Defined Functions
Triggersyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)none
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesWith clustering: 2 database servers on different computers operate on identical copies of a database
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache IoTDBDatabricksH2
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache IoTDBDatabricksH2
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