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DBMS > Derby vs. Faircom DB vs. Informix vs. Microsoft Azure Data Explorer

System Properties Comparison Derby vs. Faircom DB vs. Informix vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameDerby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonInformix  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataFully managed big data interactive analytics platform
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMS infocolumn oriented
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.30
Rank#66  Overall
#36  Relational DBMS
Score0.24
Rank#311  Overall
#44  Key-value stores
#140  Relational DBMS
Score18.85
Rank#35  Overall
#22  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Websitedb.apache.org/­derbywww.faircom.com/­products/­faircom-dbwww.ibm.com/­products/­informixazure.microsoft.com/­services/­data-explorer
Technical documentationdb.apache.org/­derby/­manuals/­index.htmldocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
docs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationFairCom CorporationIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Microsoft
Initial release1997197919842019
Current release10.17.1.0, November 2023V12, November 202014.10.FC5, November 2020cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache version 2commercial infoRestricted, free version availablecommercial infofree developer edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++C, C++ and Java
Server operating systemsAll OS with a Java VMAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
AIX
HP-UX
Linux
macOS
Solaris
Windows
hosted
Data schemeyesschema free, schema optional, schema required, partial schema,yesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyes infoSince Version 12.10 support for JSON/BSON datatypesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.yesnoyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLyesyes, ANSI SQL with proprietary extensionsyesKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBCADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesJava.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresyes info.Net, JavaScript, C/C++yesYes, possible languages: KQL, Python, R
Triggersyesyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Multi-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardFine grained access rights according to SQL-standard with additional protections for filesUsers with fine-grained authentication, authorization, and auditing controlsAzure Active Directory Authentication

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More resources
Derby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDBFaircom DB infoformerly c-treeACEInformixMicrosoft Azure Data Explorer
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