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DBMS > Amazon Neptune vs. Badger vs. Databricks vs. Faircom DB

System Properties Comparison Amazon Neptune vs. Badger vs. Databricks vs. Faircom DB

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonBadger  Xexclude from comparisonDatabricks  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.The 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.
Primary database modelGraph DBMS
RDF store
Key-value storeDocument store
Relational DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score0.14
Rank#331  Overall
#49  Key-value stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Websiteaws.amazon.com/­neptunegithub.com/­dgraph-io/­badgerwww.databricks.comwww.faircom.com/­products/­faircom-db
Technical documentationaws.amazon.com/­neptune/­developer-resourcesgodoc.org/­github.com/­dgraph-io/­badgerdocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.html
DeveloperAmazonDGraph LabsDatabricksFairCom Corporation
Initial release2017201720131979
Current releaseV12, November 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial infoRestricted, free version available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoANSI C, C++
Server operating systemshostedBSD
Linux
OS X
Solaris
Windows
hostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Data schemeschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema free, schema optional, schema required, partial schema,
Typing infopredefined data types such as float or dateyesnoyes, ANSI SQL Types, JSON, typed binary structures
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.nonoyesno
Secondary indexesnonoyesyes
SQL infoSupport of SQLnonowith Databricks SQLyes, ANSI SQL with proprietary extensions
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
GoPython
R
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Server-side scripts infoStored proceduresnonouser defined functions and aggregatesyes info.Net, JavaScript, C/C++
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.noneyesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDtunable from ACID to Eventually Consistent
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesYes, tunable from durable to delayed durability to in-memory
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noFine grained access rights according to SQL-standard with additional protections for files
More information provided by the system vendor
Amazon NeptuneBadgerDatabricksFaircom DB infoformerly c-treeACE
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon NeptuneBadgerDatabricksFaircom DB infoformerly c-treeACE
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