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DBMS > Databricks vs. Faircom DB vs. Netezza vs. ObjectBox vs. OpenQM

System Properties Comparison Databricks vs. Faircom DB vs. Netezza vs. ObjectBox vs. OpenQM

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonObjectBox  Xexclude from comparisonOpenQM infoalso called QM  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.Data warehouse and analytics appliance part of IBM PureSystemsExtremely fast embedded database for small devices, IoT and MobileQpenQM is a high-performance, self-tuning, multi-value DBMS
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Relational DBMSObject oriented DBMSMultivalue DBMS
Secondary database modelsTime Series 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
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score0.27
Rank#298  Overall
#10  Multivalue DBMS
Websitewww.databricks.comwww.faircom.com/­products/­faircom-dbwww.ibm.com/­products/­netezzaobjectbox.iowww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qm
Technical documentationdocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.objectbox.io
DeveloperDatabricksFairCom CorporationIBMObjectBox LimitedRocket Software, originally Martin Phillips
Initial release20131979200020171993
Current releaseV12, November 20203.4-12
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercialOpen Source infoApache License 2.0Open Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++C and C++
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux infoincluded in applianceAndroid
iOS
Linux
macOS
Windows
AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema free, schema optional, schema required, partial schema,yesyesyes infowith some exceptions
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyesyes
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 indexesyesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyes, ANSI SQL with proprietary extensionsyesnono
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
JDBC
ODBC
OLE DB
Proprietary native API
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C++
Fortran
Java
Lua
Perl
Python
R
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
.Net
Basic
C
Java
Objective C
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes info.Net, JavaScript, C/C++yesnoyes
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingnoneyes
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).Source-replica replicationonline/offline synchronization between client and serveryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesUsers with fine-grained authorization conceptyesAccess rights can be defined down to the item level
More information provided by the system vendor
DatabricksFaircom DB infoformerly c-treeACENetezza infoAlso called PureData System for Analytics by IBMObjectBoxOpenQM infoalso called QM
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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