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DBMS > Apache Druid vs. Hive vs. Microsoft Azure Data Explorer vs. Riak KV vs. SwayDB

System Properties Comparison Apache Druid vs. Hive vs. Microsoft Azure Data Explorer vs. Riak KV vs. SwayDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak KV  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality datadata warehouse software for querying and managing large distributed datasets, built on HadoopFully managed big data interactive analytics platformDistributed, fault tolerant key-value storeAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMS infocolumn orientedKey-value store infowith links between data sets and object tags for the creation of secondary indexesKey-value 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
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Score0.04
Rank#387  Overall
#61  Key-value stores
Websitedruid.apache.orghive.apache.orgazure.microsoft.com/­services/­data-explorerswaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software Foundation and contributorsApache Software Foundation infoinitially developed by FacebookMicrosoftOpenSource, formerly Basho TechnologiesSimer Plaha
Initial release20122012201920092018
Current release29.0.1, April 20243.1.3, April 2022cloud service with continuous releases3.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2commercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaErlangScala
Server operating systemsLinux
OS X
Unix
All OS with a Java VMhostedLinux
OS X
Data schemeyes infoschema-less columns are supportedyesFixed schema with schema-less datatypes (dynamic)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnono
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 indexesyesyesall fields are automatically indexedrestrictedno
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, RErlangno
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"none
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoAtomic execution of operations
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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and rolesAzure Active Directory Authenticationyes, using Riak Securityno

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More resources
Apache DruidHiveMicrosoft Azure Data ExplorerRiak KVSwayDB
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