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DBMS > Apache Druid vs. Graph Engine vs. Hawkular Metrics vs. KeyDB vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Druid vs. Graph Engine vs. Hawkular Metrics vs. KeyDB vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonKeyDB  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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsFully managed big data interactive analytics platform
Primary database modelRelational DBMS
Time Series DBMS
Graph DBMS
Key-value store
Time Series DBMSKey-value storeRelational 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
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.71
Rank#226  Overall
#33  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitedruid.apache.orgwww.graphengine.iowww.hawkular.orggithub.com/­Snapchat/­KeyDB
keydb.dev
azure.microsoft.com/­services/­data-explorer
Technical documentationdruid.apache.org/­docs/­latest/­designwww.graphengine.io/­docs/­manualwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.keydb.devdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsMicrosoftCommunity supported by Red HatEQ Alpha Technology Ltd.Microsoft
Initial release20122010201420192019
Current release29.0.1, April 2024cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoMIT LicenseOpen Source infoApache 2.0Open Source infoBSD-3commercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava.NET and CJavaC++
Server operating systemsLinux
OS X
Unix
.NETLinux
OS X
Windows
Linuxhosted
Data schemeyes infoschema-less columns are supportedyesschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes 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.nonononoyes
Secondary indexesyesnoyes infoby using the Redis Search moduleall fields are automatically indexed
SQL infoSupport of SQLSQL for queryingnononoKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP APIHTTP RESTProprietary protocol infoRESP - REdis Serialization ProtocoMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
F#
Visual Basic
Go
Java
Python
Ruby
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyesnoLuaYes, possible languages: KQL, Python, R
Triggersnonoyes infovia Hawkular Alertingnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioningSharding infobased on CassandraShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Strong eventual consistency with CRDTs
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoOptimistic locking, atomic execution of commands blocks and scriptsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnosimple password-based access control and ACLAzure Active Directory Authentication

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More resources
Apache DruidGraph Engine infoformer name: TrinityHawkular MetricsKeyDBMicrosoft Azure Data Explorer
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