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DBMS > Apache Druid vs. Faircom EDGE vs. Microsoft Azure Data Explorer vs. RisingWave vs. SwayDB

System Properties Comparison Apache Druid vs. Faircom EDGE vs. Microsoft Azure Data Explorer vs. RisingWave vs. SwayDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRisingWave  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsFully managed big data interactive analytics platformA distributed RDBMS for stream processing, wire-compatible with PostgreSQLAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Relational DBMS infocolumn orientedRelational DBMSKey-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
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.64
Rank#238  Overall
#110  Relational DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Websitedruid.apache.orgwww.faircom.com/­products/­faircom-edgeazure.microsoft.com/­services/­data-explorerwww.risingwave.com/­databaseswaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.risingwave.com/­docs/­current/­intro
DeveloperApache Software Foundation and contributorsFairCom CorporationMicrosoftRisingWave LabsSimer Plaha
Initial release20121979201920222018
Current release29.0.1, April 2024V3, October 2020cloud service with continuous releases1.2, September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infoRestricted, free version availablecommercialOpen Source infoApache Version 2.0Open Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++RustScala
Server operating systemsLinux
OS X
Unix
Android
Linux infoARM, x86
Raspbian
Windows
hostedDocker
Linux
macOS
Data schemeyes infoschema-less columns are supportedFlexible Schema (defined schema, partial schema, schema free)Fixed schema with schema-less datatypes (dynamic)yesschema-free
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesStandard SQL-types and JSONno
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.noyesyesnono
Secondary indexesyesyesall fields are automatically indexedyesno
SQL infoSupport of SQLSQL for queryingyes infoANSI SQL queriesKusto Query Language (KQL), SQL subsetyesno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
PostgreSQL wire protocol
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Go
Java
JavaScript (Node.js)
Python
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++Yes, possible languages: KQL, Python, RUDFs in Python or Javano
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedFile partitioning infoCustomizable business rules for partitioningSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes
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.noyesnoyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Azure Active Directory AuthenticationUsers and Rolesno

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More resources
Apache DruidFaircom EDGE infoformerly c-treeEDGEMicrosoft Azure Data ExplorerRisingWaveSwayDB
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