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DBMS > Apache IoTDB vs. Google Cloud Bigtable vs. HBase vs. Solr

System Properties Comparison Apache IoTDB vs. Google Cloud Bigtable vs. HBase vs. Solr

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHBase  Xexclude from comparisonSolr  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 FlinkGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Wide-column store based on Apache Hadoop and on concepts of BigTableA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSKey-value store
Wide column store
Wide column storeSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Websiteiotdb.apache.orgcloud.google.com/­bigtablehbase.apache.orgsolr.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.google.com/­bigtable/­docshbase.apache.org/­book.htmlsolr.apache.org/­resources.html
DeveloperApache Software FoundationGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation
Initial release2018201520082006
Current release1.1.0, April 20232.3.4, January 20219.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache version 2Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinux
Unix
Windows infousing Cygwin
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeschema-free, schema definition possibleyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesnooptions to bring your own types, AVROyes infosupports customizable data types and automatic typing
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.nononoyes
Secondary indexesyesnonoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenonoSolr Parallel SQL Interface
APIs and other access methodsJDBC
Native API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
Thrift
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesnoyes infoCoprocessors in JavaJava plugins
Triggersyesnoyesyes infoUser configurable commands triggered on index changes
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 replicasInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsSingle row ACID (across millions of columns)optimistic locking
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.yesnoyesyes
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyes

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More resources
Apache IoTDBGoogle Cloud BigtableHBaseSolr
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