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DBMS > Faircom DB vs. GeoMesa vs. Spark SQL vs. Transbase vs. YDB

System Properties Comparison Faircom DB vs. GeoMesa vs. Spark SQL vs. Transbase vs. YDB

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonGeoMesa  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparisonYDB  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Spark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMSA 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
Spatial DBMSRelational DBMSRelational DBMSDocument store
Relational DBMS
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
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Score0.33
Rank#287  Overall
#43  Document stores
#132  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbwww.geomesa.orgspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.htmlgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.geomesa.org/­documentation/­stable/­user/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.htmlydb.tech/­en/­docs
DeveloperFairCom CorporationCCRi and othersApache Software FoundationTransaction Software GmbHYandex
Initial release19792014201419872019
Current releaseV12, November 20205.0.0, May 20243.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache License 2.0Open Source infoApache 2.0commercial infofree development licenseOpen Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++ScalaScalaC and C++
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Linux
Data schemeschema free, schema optional, schema required, partial schema,yesyesyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyesyesyesyes
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.nonononono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsnoSQL-like DML and DDL statementsyesSQL-like query language (YQL)
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
RESTful HTTP API (DynamoDB compatible)
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++nonoyesno
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningdepending on storage layeryes, utilizing Spark CoreSharding
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).depending on storage layernoneSource-replica replicationActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
depending on storage layerImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentnonoyesACID
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.yesdepending on storage layernonono
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesyes infodepending on the DBMS used for storagenofine grained access rights according to SQL-standardAccess rights defined for Yandex Cloud users

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More resources
Faircom DB infoformerly c-treeACEGeoMesaSpark SQLTransbaseYDB
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