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DBMS > Amazon Neptune vs. Dragonfly vs. Google Cloud Bigtable vs. TigerGraph

System Properties Comparison Amazon Neptune vs. Dragonfly vs. Google Cloud Bigtable vs. TigerGraph

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDragonfly  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelGraph DBMS
RDF store
Key-value storeKey-value store
Wide column store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.44
Rank#255  Overall
#38  Key-value stores
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score1.44
Rank#152  Overall
#14  Graph DBMS
Websiteaws.amazon.com/­neptunegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
cloud.google.com/­bigtablewww.tigergraph.com
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.dragonflydb.io/­docscloud.google.com/­bigtable/­docsdocs.tigergraph.com
DeveloperAmazonDragonflyDB team and community contributorsGoogle
Initial release2017202320152017
Current release1.0, March 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSL 1.1commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemshostedLinuxhostedLinux
Data schemeschema-freescheme-freeschema-freeyes
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysnoyes
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.nononono
Secondary indexesnonono
SQL infoSupport of SQLnononoSQL-like query language (GSQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Proprietary protocol infoRESP - REdis Serialization ProtocolgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
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#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
Server-side scripts infoStored proceduresnoLuanoyes
Triggersnopublish/subscribe channels provide some trigger functionalitynono
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.Source-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of command blocks and scriptsAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyes
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.yesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Password-based authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control

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More resources
Amazon NeptuneDragonflyGoogle Cloud BigtableTigerGraph
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