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DBMS > Apache IoTDB vs. Databricks vs. Hazelcast vs. Microsoft Azure SQL Database

System Properties Comparison Apache IoTDB vs. Databricks vs. Hazelcast vs. Microsoft Azure SQL Database

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabricks  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  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 widely adopted in-memory data gridDatabase as a Service offering with high compatibility to Microsoft SQL Server
Primary database modelTime Series DBMSDocument store
Relational DBMS
Key-value storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Score72.95
Rank#16  Overall
#11  Relational DBMS
Websiteiotdb.apache.orgwww.databricks.comhazelcast.comazure.microsoft.com/­en-us/­products/­azure-sql/­database
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databricks.comhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­azure-sql
DeveloperApache Software FoundationDatabricksHazelcastMicrosoft
Initial release2018201320082010
Current release1.1.0, April 20235.3.6, November 2023V12
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)hostedAll OS with a Java VMhosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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.noyesyes infothe object must implement a serialization strategyyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagewith Databricks SQLSQL-like query languageyes
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Python
R
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesyes infoEvent Listeners, Executor ServicesTransact SQL
Triggersyesyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesyes infoReplicated Mapyes, with always 3 replicas available
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDone or two-phase-commit; repeatable reads; read commitedACID
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.yesnoyes
User concepts infoAccess controlyesRole-based access controlfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache IoTDBDatabricksHazelcastMicrosoft Azure SQL Database infoformerly SQL Azure
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache IoTDBDatabricksHazelcastMicrosoft Azure SQL Database infoformerly SQL Azure
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