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DBMS > Apache IoTDB vs. Databricks vs. Hazelcast vs. IBM Cloudant vs. Sphinx

System Properties Comparison Apache IoTDB vs. Databricks vs. Hazelcast vs. IBM Cloudant vs. Sphinx

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabricks  Xexclude from comparisonHazelcast  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonSphinx  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 based on Apache CouchDBOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSDocument store
Relational DBMS
Key-value storeDocument storeSearch engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12
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
Score5.46
Rank#61  Overall
#7  Key-value stores
Score2.75
Rank#104  Overall
#19  Document stores
Score5.95
Rank#55  Overall
#5  Search engines
Websiteiotdb.apache.orgwww.databricks.comhazelcast.comwww.ibm.com/­products/­cloudantsphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databricks.comhazelcast.org/­imdg/­docscloud.ibm.com/­docs/­Cloudantsphinxsearch.com/­docs
DeveloperApache Software FoundationDatabricksHazelcastIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014Sphinx Technologies Inc.
Initial release20182013200820102001
Current release1.1.0, April 20235.3.6, November 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaErlangC++
Server operating systemsAll OS with a Java VM (>= 1.8)hostedAll OS with a Java VMhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnono
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 strategyno
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagewith Databricks SQLSQL-like query languagenoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP/JSON APIProprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Python
R
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
Java
JavaScript
Objective-C
PHP
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesyes infoEvent Listeners, Executor ServicesView functions (Map-Reduce) in JavaScriptno
Triggersyesyes infoEventsyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
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 MapMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyesno
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 AlgorithmEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDone or two-phase-commit; repeatable reads; read commitedno infoatomic operations within a document possibleno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoOptimistic lockingyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
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 access controlAccess rights for users can be defined per databaseno
More information provided by the system vendor
Apache IoTDBDatabricksHazelcastIBM CloudantSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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