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DBMS > Faircom DB vs. Microsoft Azure Table Storage vs. Solr

System Properties Comparison Faircom DB vs. Microsoft Azure Table Storage vs. Solr

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Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A Wide Column Store for rapid development using massive semi-structured datasetsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelKey-value store
Relational DBMS
Wide column storeSearch engine
Secondary database modelsSpatial DBMS
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
Score4.48
Rank#75  Overall
#6  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.faircom.com/­products/­faircom-dbazure.microsoft.com/­en-us/­services/­storage/­tablessolr.apache.org
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlsolr.apache.org/­resources.html
DeveloperFairCom CorporationMicrosoftApache Software Foundation
Initial release197920122006
Current releaseV12, November 20209.6.0, April 2024
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++Java
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema free, schema optional, schema required, partial schema,schema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyesyes infosupports customizable data types and automatic typing
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.nonoyes
Secondary indexesyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsnoSolr Parallel SQL Interface
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
RESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languages.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
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++noJava plugins
Triggersyesnoyes infoUser configurable commands triggered on index changes
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 serviceSharding
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.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually Consistentoptimistic lockingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentYes, 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.yesnoyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesAccess rights based on private key authentication or shared access signaturesyes

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More resources
Faircom DB infoformerly c-treeACEMicrosoft Azure Table StorageSolr
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