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DBMS > Apache IoTDB vs. Databricks vs. Google Cloud Bigtable vs. Hazelcast vs. IBM Cloudant

System Properties Comparison Apache IoTDB vs. Databricks vs. Google Cloud Bigtable vs. Hazelcast vs. IBM Cloudant

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabricks  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparisonIBM Cloudant  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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A widely adopted in-memory data gridDatabase as a Service offering based on Apache CouchDB
Primary database modelTime Series DBMSDocument store
Relational DBMS
Key-value store
Wide column store
Key-value storeDocument store
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
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score2.75
Rank#104  Overall
#19  Document stores
Websiteiotdb.apache.orgwww.databricks.comcloud.google.com/­bigtablehazelcast.comwww.ibm.com/­products/­cloudant
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databricks.comcloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docscloud.ibm.com/­docs/­Cloudant
DeveloperApache Software FoundationDatabricksGoogleHazelcastIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014
Initial release20182013201520082010
Current release1.1.0, April 20235.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaErlang
Server operating systemsAll OS with a Java VM (>= 1.8)hostedhostedAll OS with a Java VMhosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyesno
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.noyesnoyes infothe object must implement a serialization strategyno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagewith Databricks SQLnoSQL-like query languageno
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Python
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
Java
JavaScript
Objective-C
PHP
Ruby
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesnoyes infoEvent Listeners, Executor ServicesView functions (Map-Reduce) in JavaScript
Triggersyesnoyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoReplicated MapMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate 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 datanoACIDAtomic single-row operationsone or two-phase-commit; repeatable reads; read commitedno infoatomic operations within a document possible
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infoOptimistic locking
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyesno
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlAccess rights for users can be defined per database
More information provided by the system vendor
Apache IoTDBDatabricksGoogle Cloud BigtableHazelcastIBM Cloudant
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache IoTDBDatabricksGoogle Cloud BigtableHazelcastIBM Cloudant
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