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DBMS > Faircom DB vs. Solr vs. Valentina Server vs. YottaDB

System Properties Comparison Faircom DB vs. Solr vs. Valentina Server vs. YottaDB

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Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonSolr  Xexclude from comparisonValentina Server  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A widely used distributed, scalable search engine based on Apache LuceneObject-relational database and reports serverA fast and solid embedded Key-value store
Primary database modelKey-value store
Relational DBMS
Search engineRelational DBMSKey-value store
Secondary database modelsSpatial DBMSRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.21
Rank#325  Overall
#144  Relational DBMS
Score0.28
Rank#306  Overall
#44  Key-value stores
Websitewww.faircom.com/­products/­faircom-dbsolr.apache.orgwww.valentina-db.netyottadb.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlsolr.apache.org/­resources.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.phpyottadb.com/­resources/­documentation
DeveloperFairCom CorporationApache Software FoundationParadigma SoftwareYottaDB, LLC
Initial release1979200619992001
Current releaseV12, November 20209.6.1, May 20245.7.5
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache Version 2commercialOpen Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++JavaC
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Docker
Linux
Data schemeschema free, schema optional, schema required, partial schema,yes infoDynamic Fields enables on-the-fly addition of new fieldsyesschema-free
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyes infosupports customizable data types and automatic typingyesno
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.noyesno
Secondary indexesyesyes infoAll search fields are automatically indexedyesno
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsSolr Parallel SQL Interfaceyesby using the Octo plugin
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Java API
RESTful HTTP/JSON API
ODBCPostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++Java pluginsyes
Triggersyesyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding
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).yesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Foreign keys infoReferential integrityyesnoyes
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 datayesyes
Durability infoSupport for making data persistentYes, 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.yesyesyesyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesyesfine grained access rights according to SQL-standardUsers and groups based on OS-security mechanisms

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More resources
Faircom DB infoformerly c-treeACESolrValentina ServerYottaDB
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