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DBMS > Apache Druid vs. Faircom EDGE vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB vs. SpaceTime

System Properties Comparison Apache Druid vs. Faircom EDGE vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB vs. SpaceTime

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpaceTime  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 platformWidely used in-process key-value storeSpaceTime is a spatio-temporal DBMS with a focus on performance.
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Relational DBMS infocolumn orientedKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Spatial 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 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
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score0.00
Rank#383  Overall
#7  Spatial DBMS
Websitedruid.apache.orgwww.faircom.com/­products/­faircom-edgeazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.mireo.com/­spacetime
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.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperApache Software Foundation and contributorsFairCom CorporationMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleMireo
Initial release20121979201919942020
Current release29.0.1, April 2024V3, October 2020cloud service with continuous releases18.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infoRestricted, free version availablecommercialOpen Source infocommercial license availablecommercial
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 languageJavaANSI C, C++C, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemsLinux
OS X
Unix
Android
Linux infoARM, x86
Raspbian
Windows
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
Data schemeyes infoschema-less columns are supportedFlexible Schema (defined schema, partial schema, schema free)Fixed schema with schema-less datatypes (dynamic)schema-freeyes
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-typesnoyes
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.noyesyesyes infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesall fields are automatically indexedyesno
SQL infoSupport of SQLSQL for queryingyes infoANSI SQL queriesKusto Query Language (KQL), SQL subsetyes infoSQL interfaced based on SQLite is availableA subset of ANSI SQL is implemented
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
RESTful HTTP API
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
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C#
C++
Python
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++Yes, possible languages: KQL, Python, Rnono
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoonly for the SQL APIno
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 servicenoneFixed-grid hypercubes
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.Source-replica replicationReal-time block device replication (DRBD)
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 datanoACIDnoACIDno
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.noyesnoyesno
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 Authenticationnoyes

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More resources
Apache DruidFaircom EDGE infoformerly c-treeEDGEMicrosoft Azure Data ExplorerOracle Berkeley DBSpaceTime
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