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DBMS > Apache Druid vs. FeatureBase vs. Microsoft Azure Data Explorer vs. SpaceTime vs. Vitess

System Properties Comparison Apache Druid vs. FeatureBase vs. Microsoft Azure Data Explorer vs. SpaceTime vs. Vitess

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFeatureBase  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpaceTime  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Fully managed big data interactive analytics platformSpaceTime is a spatio-temporal DBMS with a focus on performance.Scalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMS infocolumn orientedSpatial DBMSRelational DBMS
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
Relational DBMSDocument store
Spatial DBMS
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
Score0.22
Rank#309  Overall
#139  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#383  Overall
#7  Spatial DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitedruid.apache.orgwww.featurebase.comazure.microsoft.com/­services/­data-explorerwww.mireo.com/­spacetimevitess.io
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.featurebase.comdocs.microsoft.com/­en-us/­azure/­data-explorervitess.io/­docs
DeveloperApache Software Foundation and contributorsMolecula and Pilosa Open Source ContributorsMicrosoftMireoThe Linux Foundation, PlanetScale
Initial release20122017201920202013
Current release29.0.1, April 20242022, May 2022cloud service with continuous releases15.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialcommercialOpen Source infoApache Version 2.0, commercial licenses available
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 languageJavaGoC++Go
Server operating systemsLinux
OS X
Unix
Linux
macOS
hostedLinuxDocker
Linux
macOS
Data schemeyes infoschema-less columns are supportedyesFixed schema with schema-less datatypes (dynamic)yesyes
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-typesyesyes
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.nonoyesno
Secondary indexesyesnoall fields are automatically indexednoyes
SQL infoSupport of SQLSQL for queryingSQL queriesKusto Query Language (KQL), SQL subsetA subset of ANSI SQL is implementedyes infowith proprietary extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC
JDBC
Kafka Connector
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rnoyes infoproprietary syntax
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoImplicit feature of the cloud serviceFixed-grid hypercubesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Real-time block device replication (DRBD)Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesnonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnonoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyes, using Linux fsyncyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAzure Active Directory AuthenticationyesUsers with fine-grained authorization concept infono user groups or roles

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More resources
Apache DruidFeatureBaseMicrosoft Azure Data ExplorerSpaceTimeVitess
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