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DBMS > Amazon Neptune vs. Databricks vs. Dragonfly vs. Riak TS

System Properties Comparison Amazon Neptune vs. Databricks vs. Dragonfly vs. Riak TS

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDatabricks  Xexclude from comparisonDragonfly  Xexclude from comparisonRiak TS  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudThe 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.A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelGraph DBMS
RDF store
Document store
Relational DBMS
Key-value storeTime Series 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
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.41
Rank#266  Overall
#38  Key-value stores
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Websiteaws.amazon.com/­neptunewww.databricks.comgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.databricks.comwww.dragonflydb.io/­docswww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperAmazonDatabricksDragonflyDB team and community contributorsOpen Source, formerly Basho Technologies
Initial release2017201320232015
Current release1.0, March 20233.0.0, September 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSL 1.1Open Source
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Erlang
Server operating systemshostedhostedLinuxLinux
OS X
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)scheme-freeschema-free
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysno
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.noyesnono
Secondary indexesnoyesnorestricted
SQL infoSupport of SQLnowith Databricks SQLnoyes, limited
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocolHTTP API
Native Erlang Interface
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Python
R
Scala
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresnouser defined functions and aggregatesLuaErlang
Triggersnopublish/subscribe channels provide some trigger functionalityyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
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.yesSource-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnono infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic execution of command blocks and scriptsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, strict serializability by the serveryes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Password-based authenticationno
More information provided by the system vendor
Amazon NeptuneDatabricksDragonflyRiak TS
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon NeptuneDatabricksDragonflyRiak TS
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