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DBMS > Faircom DB vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. Prometheus vs. Riak KV

System Properties Comparison Faircom DB vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. Prometheus vs. Riak KV

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Data Explorer  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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully managed big data interactive analytics platformOpen-source Time Series DBMS and monitoring systemDistributed, fault tolerant key-value store
Primary database modelKey-value store
Relational DBMS
Key-value store
Wide column store
Relational DBMS infocolumn orientedTime 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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitewww.faircom.com/­products/­faircom-dbcloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorerprometheus.io
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerprometheus.io/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperFairCom CorporationGoogleMicrosoftOpenSource, formerly Basho Technologies
Initial release19792015201920152009
Current releaseV12, November 2020cloud service with continuous releases3.2.0, December 2022
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialcommercialOpen Source infoApache 2.0Open Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++GoErlang
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedhostedLinux
Windows
Linux
OS X
Data schemeschema free, schema optional, schema required, partial schema,schema-freeFixed schema with schema-less datatypes (dynamic)yesschema-free
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesNumeric 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.nonoyesno infoImport of XML data possibleno
Secondary indexesyesnoall fields are automatically indexednorestricted
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsnoKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
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
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.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++noYes, possible languages: KQL, Python, RnoErlang
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes 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 partitioningShardingSharding infoImplicit feature of the cloud serviceShardingSharding 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).Internal replication in Colossus, and regional replication between two clusters in different zonesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoby Federationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)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 ConsistentAtomic single-row operationsnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnonono
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory Authenticationnoyes, using Riak Security

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More resources
Faircom DB infoformerly c-treeACEGoogle Cloud BigtableMicrosoft Azure Data ExplorerPrometheusRiak KV
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