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DBMS > Faircom DB vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB vs. Prometheus vs. Riak KV

System Properties Comparison Faircom DB vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB vs. Prometheus vs. Riak KV

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonPrometheus  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Fully managed big data interactive analytics platformWidely used in-process key-value storeOpen-source Time Series DBMS and monitoring systemDistributed, fault tolerant key-value store
Primary database modelKey-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
Time Series DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
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
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitewww.faircom.com/­products/­faircom-dbazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlprometheus.io
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlprometheus.io/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperFairCom CorporationMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleOpenSource, formerly Basho Technologies
Initial release19792019199420152009
Current releaseV12, November 2020cloud service with continuous releases18.1.40, May 20203.2.0, December 2022
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialOpen Source infocommercial license availableOpen Source infoApache 2.0Open Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++C, Java, C++ (depending on the Berkeley DB edition)GoErlang
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
Windows
Linux
OS X
Data schemeschema free, schema optional, schema required, partial schema,Fixed schema with schema-less datatypes (dynamic)schema-freeyesschema-free
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoNumeric data onlyno
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.noyesyes infoonly with the Berkeley DB XML editionno infoImport of XML data possibleno
Secondary indexesyesall fields are automatically indexedyesnorestricted
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsKusto Query Language (KQL), SQL subsetyes infoSQL interfaced based on SQLite is availablenono
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP/JSON APIHTTP API
Native Erlang Interface
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.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
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++Yes, possible languages: KQL, Python, RnonoErlang
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoonly for the SQL APInoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infoImplicit feature of the cloud servicenoneShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationyes infoby Federationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Immediate Consistency
noneEventual Consistency
Foreign keys infoReferential integrityyesnononono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesAzure Active Directory Authenticationnonoyes, using Riak Security

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More resources
Faircom DB infoformerly c-treeACEMicrosoft Azure Data ExplorerOracle Berkeley DBPrometheusRiak KV
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