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DBMS > Apache IoTDB vs. Databricks vs. HBase vs. Sqrrl vs. ToroDB

System Properties Comparison Apache IoTDB vs. Databricks vs. HBase vs. Sqrrl vs. ToroDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonSqrrl  Xexclude from comparisonToroDB  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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.Wide-column store based on Apache Hadoop and on concepts of BigTableAdaptable, secure NoSQL built on Apache AccumuloA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelTime Series DBMSDocument store
Relational DBMS
Wide column storeDocument store
Graph DBMS
Key-value store
Wide column store
Document store
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
Score27.97
Rank#26  Overall
#2  Wide column stores
Websiteiotdb.apache.orgwww.databricks.comhbase.apache.orgsqrrl.comgithub.com/­torodb/­server
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databricks.comhbase.apache.org/­book.html
DeveloperApache Software FoundationDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetAmazon infooriginally Sqrrl Data, Inc.8Kdata
Initial release20182013200820122016
Current release1.1.0, April 20232.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache version 2commercialOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinux
Unix
Windows infousing Cygwin
LinuxAll OS with a Java 7 VM
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleschema-freeschema-free
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes infostring, integer, double, boolean, date, object_id
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.noyesnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query languagewith Databricks SQLnono
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Python
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesyes infoCoprocessors in Javano
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infomaking use of HadoopSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesMulti-source replication
Source-replica replication
selectable replication factor infomaking use of HadoopSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDSingle row ACID (across millions of columns)Atomic updates per row, document, or graph entityno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnoyes
User concepts infoAccess controlyesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)Access rights for users and roles
More information provided by the system vendor
Apache IoTDBDatabricksHBaseSqrrlToroDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache IoTDBDatabricksHBaseSqrrlToroDB
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