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DBMS > Apache Druid vs. EsgynDB vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage vs. Riak KV

System Properties Comparison Apache Druid vs. EsgynDB vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage vs. Riak KV

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEsgynDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFully managed big data interactive analytics platformA Wide Column Store for rapid development using massive semi-structured datasetsDistributed, fault tolerant key-value store
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMS infocolumn orientedWide column storeKey-value store infowith links between data sets and object tags for the creation of secondary indexes
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
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitedruid.apache.orgwww.esgyn.cnazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperApache Software Foundation and contributorsEsgynMicrosoftMicrosoftOpenSource, formerly Basho Technologies
Initial release20122015201920122009
Current release29.0.1, April 2024cloud service with continuous releases3.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialcommercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaErlang
Server operating systemsLinux
OS X
Unix
LinuxhostedhostedLinux
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-typesyesno
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.nonoyesnono
Secondary indexesyesyesall fields are automatically indexednorestricted
SQL infoSupport of SQLSQL for queryingyesKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIHTTP API
Native Erlang Interface
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
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
Server-side scripts infoStored proceduresnoJava Stored ProceduresYes, possible languages: KQL, Python, RnoErlang
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication between multi datacentersyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnonono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnooptimistic lockingno
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.nononono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAzure Active Directory AuthenticationAccess rights based on private key authentication or shared access signaturesyes, using Riak Security

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More resources
Apache DruidEsgynDBMicrosoft Azure Data ExplorerMicrosoft Azure Table StorageRiak KV
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