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DBMS > Apache Druid vs. Apache IoTDB vs. BigchainDB vs. Microsoft Azure Data Explorer vs. Sqrrl

System Properties Comparison Apache Druid vs. Apache IoTDB vs. BigchainDB vs. Microsoft Azure Data Explorer vs. Sqrrl

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache IoTDB  Xexclude from comparisonBigchainDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSqrrl  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.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsFully managed big data interactive analytics platformAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSDocument storeRelational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.85
Rank#208  Overall
#35  Document stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitedruid.apache.orgiotdb.apache.orgwww.bigchaindb.comazure.microsoft.com/­services/­data-explorersqrrl.com
Technical documentationdruid.apache.org/­docs/­latest/­designiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlbigchaindb.readthedocs.io/­en/­latestdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsApache Software FoundationMicrosoftAmazon infooriginally Sqrrl Data, Inc.
Initial release20122018201620192012
Current release29.0.1, April 20241.1.0, April 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0Open Source infoAGPL v3commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaPythonJava
Server operating systemsLinux
OS X
Unix
All OS with a Java VM (>= 1.8)LinuxhostedLinux
Data schemeyes infoschema-less columns are supportedyesschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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 indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL for queryingSQL-like query languagenoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
Native API
CLI Client
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
Go
Haskell
Java
JavaScript
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoyesYes, possible languages: KQL, Python, Rno
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infoImplicit feature of the cloud serviceSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and SparknoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes,with MongoDB ord RethinkDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesyesAzure Active Directory AuthenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Apache DruidApache IoTDBBigchainDBMicrosoft Azure Data ExplorerSqrrl
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