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DBMS > Apache Druid vs. Cloudflare Workers KV vs. eXtremeDB vs. Heroic vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Druid vs. Cloudflare Workers KV vs. eXtremeDB vs. Heroic vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisoneXtremeDB  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Natively in-memory DBMS with options for persistency, high-availability and clusteringTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platform
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeRelational DBMS
Time Series DBMS
Time Series DBMSRelational DBMS infocolumn oriented
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
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.32
Rank#283  Overall
#40  Key-value stores
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitedruid.apache.orgwww.cloudflare.com/­developer-platform/­workers-kvwww.mcobject.comgithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorer
Technical documentationdruid.apache.org/­docs/­latest/­designdevelopers.cloudflare.com/­kv/­apiwww.mcobject.com/­docs/­extremedb.htmspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsCloudflareMcObjectSpotifyMicrosoft
Initial release20122018200120142019
Current release29.0.1, April 20248.2, 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++Java
Server operating systemsLinux
OS X
Unix
hostedAIX
HP-UX
Linux
macOS
Solaris
Windows
hosted
Data schemeyes infoschema-less columns are supportedschema-freeyesschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesnoyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonono infosupport of XML interfaces availablenoyes
Secondary indexesyesnoyesyes infovia Elasticsearchall fields are automatically indexed
SQL infoSupport of SQLSQL for queryingnoyes infowith the option: eXtremeSQLnoKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HTTP REST
Proprietary protocol
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
.Net
C
C#
C++
Java
Lua
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnonoyesnoYes, possible languages: KQL, Python, R
Triggersnonoyes infoby defining eventsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning / shardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
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.nonoyesnono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAzure Active Directory Authentication
More information provided by the system vendor
Apache DruidCloudflare Workers KVeXtremeDBHeroicMicrosoft Azure Data Explorer
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more

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Apache DruidCloudflare Workers KVeXtremeDBHeroicMicrosoft Azure Data Explorer
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