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DBMS > Apache IoTDB vs. Apache Pinot vs. Databricks

System Properties Comparison Apache IoTDB vs. Apache Pinot vs. Databricks

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonApache Pinot  Xexclude from comparisonDatabricks  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 FlinkRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyThe 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.
Primary database modelTime Series DBMSRelational DBMSDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Websiteiotdb.apache.orgpinot.apache.orgwww.databricks.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.pinot.apache.orgdocs.databricks.com
DeveloperApache Software FoundationApache Software Foundation and contributorsDatabricks
Initial release201820152013
Current release1.1.0, April 20231.0.0, September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java JDK11 or higherhosted
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)
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.noyes
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query languagewith Databricks SQL
APIs and other access methodsJDBC
Native API
JDBCJDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
Python
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functions and aggregates
Triggersyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlyes
More information provided by the system vendor
Apache IoTDBApache PinotDatabricks
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache IoTDBApache PinotDatabricks
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