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

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

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonDatabricks  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonHBase  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLThe 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 BigTable
Primary database modelRelational DBMSDocument store
Relational DBMS
Key-value store
Relational DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#288  Overall
#131  Relational DBMS
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
Websitebrytlyt.iowww.databricks.comwww.faircom.com/­products/­faircom-dbhbase.apache.org
Technical documentationdocs.brytlyt.iodocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlhbase.apache.org/­book.html
DeveloperBrytlytDatabricksFairCom CorporationApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2016201319792008
Current release5.0, August 2023V12, November 20202.3.4, January 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial infoRestricted, free version availableOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ and CUDAANSI C, C++Java
Server operating systemsLinux
OS X
Windows
hostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
Unix
Windows infousing Cygwin
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema free, schema optional, schema required, partial schema,schema-free, schema definition possible
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresoptions to bring your own types, AVRO
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.yes infospecific XML-type available, but no XML query functionality.yesnono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyeswith Databricks SQLyes, ANSI SQL with proprietary extensionsno
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
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
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Python
R
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLuser defined functions and aggregatesyes info.Net, JavaScript, C/C++yes infoCoprocessors in Java
Triggersyesyesyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesyes, 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
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
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 or Eventual Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDtunable from ACID to Eventually ConsistentSingle row ACID (across millions of columns)
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesYes, 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.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardFine grained access rights according to SQL-standard with additional protections for filesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC
More information provided by the system vendor
BrytlytDatabricksFaircom DB infoformerly c-treeACEHBase
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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BrytlytDatabricksFaircom DB infoformerly c-treeACEHBase
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