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DBMS > Databricks vs. Datomic vs. Faircom DB vs. Faircom EDGE

System Properties Comparison Databricks vs. Datomic vs. Faircom DB vs. Faircom EDGE

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDatomic  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  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.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store
Relational DBMS
Key-value store
Relational 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
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Websitewww.databricks.comwww.datomic.comwww.faircom.com/­products/­faircom-dbwww.faircom.com/­products/­faircom-edge
Technical documentationdocs.databricks.comdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html
DeveloperDatabricksCognitectFairCom CorporationFairCom Corporation
Initial release2013201219791979
Current release1.0.7075, December 2023V12, November 2020V3, October 2020
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freecommercial infoRestricted, free version availablecommercial infoRestricted, free version available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureANSI C, C++ANSI C, C++
Server operating systemshostedAll OS with a Java VMAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Android
Linux infoARM, x86
Raspbian
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema free, schema optional, schema required, partial schema,Flexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyes, ANSI Standard SQL Types
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
SQL infoSupport of SQLwith Databricks SQLnoyes, ANSI SQL with proprietary extensionsyes infoANSI SQL queries
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Supported programming languagesPython
R
Scala
Clojure
Java
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoTransaction Functionsyes info.Net, JavaScript, C/C++yes info.Net, JavaScript, C/C++
TriggersBy using transaction functionsyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningFile partitioning infoCustomizable business rules for partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone infoBut extensive use of caching in the application peersyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yes infoSynchronous and asynchronous realtime replication based on transaction logs
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyesyes infowhen using SQL
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDtunable from ACID to Eventually ConsistentACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoacross SQL and NoSQL
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)Yes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.
More information provided by the system vendor
DatabricksDatomicFaircom DB infoformerly c-treeACEFaircom EDGE infoformerly c-treeEDGE
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDatomicFaircom DB infoformerly c-treeACEFaircom EDGE infoformerly c-treeEDGE
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