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DBMS > Databricks vs. Faircom DB vs. GeoMesa vs. Solr

System Properties Comparison Databricks vs. Faircom DB vs. GeoMesa vs. Solr

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGeoMesa  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Native 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.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Spatial DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.databricks.comwww.faircom.com/­products/­faircom-dbwww.geomesa.orgsolr.apache.org
Technical documentationdocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.geomesa.org/­documentation/­stable/­user/­index.htmlsolr.apache.org/­resources.html
DeveloperDatabricksFairCom CorporationCCRi and othersApache Software Foundation
Initial release2013197920142006
Current releaseV12, November 20205.0.0, May 20249.6.1, May 2024
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availableOpen Source infoApache License 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++ScalaJava
Server operating systemshostedAIX
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)
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema free, schema optional, schema required, partial schema,yesyes 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.yesnonoyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLyes, ANSI SQL with proprietary extensionsnoSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Java API
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
.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
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes 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 partitioningdepending on storage layerSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, 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 layeryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
depending on storage layerEventual Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually Consistentnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, 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.noyesdepending on storage layeryes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesyes infodepending on the DBMS used for storageyes
More information provided by the system vendor
DatabricksFaircom DB infoformerly c-treeACEGeoMesaSolr
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFaircom DB infoformerly c-treeACEGeoMesaSolr
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