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DBMS > Apache Druid vs. Faircom DB vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. SpaceTime

System Properties Comparison Apache Druid vs. Faircom DB vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. SpaceTime

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpaceTime  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Common in IBM host environments, 2 different versions for host and Windows/LinuxFully managed big data interactive analytics platformSpaceTime is a spatio-temporal DBMS with a focus on performance.
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Relational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRelational DBMS infocolumn orientedSpatial DBMS
Secondary database modelsDocument store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
Document 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
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score128.46
Rank#8  Overall
#5  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#383  Overall
#7  Spatial DBMS
Websitedruid.apache.orgwww.faircom.com/­products/­faircom-dbwww.ibm.com/­products/­db2azure.microsoft.com/­services/­data-explorerwww.mireo.com/­spacetime
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.ibm.com/­docs/­en/­db2docs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsFairCom CorporationIBMMicrosoftMireo
Initial release201219791983 infohost version20192020
Current release29.0.1, April 2024V12, November 202012.1, October 2016cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infoRestricted, free version availablecommercial infofree version is availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++C and C++C++
Server operating systemsLinux
OS X
Unix
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
AIX
HP-UX
Linux
Solaris
Windows
z/OS
hostedLinux
Data schemeyes infoschema-less columns are supportedschema free, schema optional, schema required, partial schema,yesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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 indexesyesyesyesall fields are automatically indexedno
SQL infoSupport of SQLSQL for queryingyes, ANSI SQL with proprietary extensionsyesKusto Query Language (KQL), SQL subsetA subset of ANSI SQL is implemented
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Python
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++yesYes, possible languages: KQL, Python, Rno
Triggersnoyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infoonly with Windows/Unix/Linux VersionSharding infoImplicit feature of the cloud serviceFixed-grid hypercubes
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yes infowith separate tools (MQ, InfoSphere)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Real-time block device replication (DRBD)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually ConsistentACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
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-standard with additional protections for filesfine grained access rights according to SQL-standardAzure Active Directory Authenticationyes

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More resources
Apache DruidFaircom DB infoformerly c-treeACEIBM Db2 infoformerly named DB2 or IBM Database 2Microsoft Azure Data ExplorerSpaceTime
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