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DBMS > Databricks vs. Faircom DB vs. Teradata Aster vs. TinkerGraph

System Properties Comparison Databricks vs. Faircom DB vs. Teradata Aster vs. TinkerGraph

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTinkerGraph  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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.Platform for big data analytics on multistructured data sources and typesA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Relational DBMSGraph 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
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websitewww.databricks.comwww.faircom.com/­products/­faircom-dbtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationdocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.html
DeveloperDatabricksFairCom CorporationTeradata
Initial release2013197920052009
Current releaseV12, November 2020
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercialOpen Source infoApache 2.0
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++Java
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema free, schema optional, schema required, partial schema,Flexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeschema-free
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.yesnoyes infoin Aster File Storeno
Secondary indexesyesyesyesno
SQL infoSupport of SQLwith Databricks SQLyes, ANSI SQL with proprietary extensionsyesno
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
ADO.NET
JDBC
ODBC
OLE DB
TinkerPop 3
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C#
C++
Java
Python
R
Groovy
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes info.Net, JavaScript, C/C++R packagesno
Triggersyesnono
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).yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoSQL Map-Reduce Frameworkno
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 Consistency depending on configurationnone
Foreign keys infoReferential integrityyesnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesno
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesfine grained access rights according to SQL-standardno
More information provided by the system vendor
DatabricksFaircom DB infoformerly c-treeACETeradata AsterTinkerGraph
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFaircom DB infoformerly c-treeACETeradata AsterTinkerGraph
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