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DBMS > Databricks vs. Faircom DB vs. HBase vs. Interbase

System Properties Comparison Databricks vs. Faircom DB vs. HBase vs. Interbase

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonHBase  Xexclude from comparisonInterbase  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.Wide-column store based on Apache Hadoop and on concepts of BigTableLight-weight proven RDBMS infooriginally from Borland
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Wide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score4.61
Rank#72  Overall
#39  Relational DBMS
Websitewww.databricks.comwww.faircom.com/­products/­faircom-dbhbase.apache.orgwww.embarcadero.com/­products/­interbase
Technical documentationdocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlhbase.apache.org/­book.htmldocs.embarcadero.com/­products/­interbase
DeveloperDatabricksFairCom CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetEmbarcadero
Initial release2013197920081984
Current releaseV12, November 20202.3.4, January 2021InterBase 2020, December 2019
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availableOpen Source infoApache version 2commercial
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++JavaC
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
Unix
Windows infousing Cygwin
Android
iOS
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema free, schema optional, schema required, partial schema,schema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresoptions to bring your own types, AVROyes
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.yesnonono infoexport as XML data possible
Secondary indexesyesyesnoyes
SQL infoSupport of SQLwith Databricks SQLyes, ANSI SQL with proprietary extensionsnoyes
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 API
Thrift
ADO.NET
JDBC
ODBC
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes info.Net, JavaScript, C/C++yes infoCoprocessors in Javayes infoInterbase procedure and trigger language
Triggersyesyesyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingnone
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).Multi-source replication
Source-replica replication
Interbase Change Views
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMultiversion concurreny control
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.noyesyesyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksFaircom DB infoformerly c-treeACEHBaseInterbase
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFaircom DB infoformerly c-treeACEHBaseInterbase
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