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DBMS > Apache IoTDB vs. BigObject vs. Databricks vs. Solr

System Properties Comparison Apache IoTDB vs. BigObject vs. Databricks vs. Solr

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBigObject  Xexclude from comparisonDatabricks  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 FlinkAnalytic DBMS for real-time computations and queriesThe 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 used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSRelational DBMS infoa hierachical model (tree) can be imposedDocument store
Relational DBMS
Search engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteiotdb.apache.orgbigobject.iowww.databricks.comsolr.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bigobject.iodocs.databricks.comsolr.apache.org/­resources.html
DeveloperApache Software FoundationBigObject, Inc.DatabricksApache Software Foundation
Initial release2018201520132006
Current release1.1.0, April 20239.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availablecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)yes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyes 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.nonoyesyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementswith Databricks SQLSolr Parallel SQL Interface
APIs and other access methodsJDBC
Native API
fluentd
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Python
R
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesLuauser defined functions and aggregatesJava plugins
Triggersyesnoyes 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)noneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknospark-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
noneImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes
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.yesyesnoyes
User concepts infoAccess controlyesnoyes
More information provided by the system vendor
Apache IoTDBBigObjectDatabricksSolr
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache IoTDBBigObjectDatabricksSolr
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