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DBMS > Faircom EDGE vs. Solr vs. Yaacomo vs. YDB

System Properties Comparison Faircom EDGE vs. Solr vs. Yaacomo vs. YDB

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Editorial information provided by DB-Engines
NameFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSolr  Xexclude from comparisonYaacomo  Xexclude from comparisonYDB  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA widely used distributed, scalable search engine based on Apache LuceneOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computingA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelKey-value store
Relational DBMS
Search engineRelational DBMSDocument store
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.33
Rank#287  Overall
#43  Document stores
#132  Relational DBMS
Websitewww.faircom.com/­products/­faircom-edgesolr.apache.orgyaacomo.comgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlsolr.apache.org/­resources.htmlydb.tech/­en/­docs
DeveloperFairCom CorporationApache Software FoundationQ2WEB GmbHYandex
Initial release1979200620092019
Current releaseV3, October 20209.6.1, May 2024
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache Version 2commercialOpen Source infoApache 2.0; commercial license available
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++Java
Server operating systemsAndroid
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Android
Linux
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yes infoDynamic Fields enables on-the-fly addition of new fieldsyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyes, ANSI Standard SQL Typesyes infosupports customizable data types and automatic typingyesyes
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.yesyesnono
Secondary indexesyesyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLyes infoANSI SQL queriesSolr Parallel SQL InterfaceyesSQL-like query language (YQL)
APIs and other access methodsADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++Java pluginsno
Triggersyesyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsyesSource-replica replicationActive-passive shard replication
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 systemImmediate Consistency
Tunable Consistency
Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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 user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.yesfine grained access rights according to SQL-standardAccess rights defined for Yandex Cloud users

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More resources
Faircom EDGE infoformerly c-treeEDGESolrYaacomoYDB
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