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DBMS > Amazon Neptune vs. Badger vs. DolphinDB vs. Firebase Realtime Database vs. Google Cloud Bigtable

System Properties Comparison Amazon Neptune vs. Badger vs. DolphinDB vs. Firebase Realtime Database vs. Google Cloud Bigtable

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonBadger  Xexclude from comparisonDolphinDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelGraph DBMS
RDF store
Key-value storeTime Series DBMSDocument storeKey-value store
Wide column store
Secondary database modelsRelational 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
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websiteaws.amazon.com/­neptunegithub.com/­dgraph-io/­badgerwww.dolphindb.comfirebase.google.com/­products/­realtime-databasecloud.google.com/­bigtable
Technical documentationaws.amazon.com/­neptune/­developer-resourcesgodoc.org/­github.com/­dgraph-io/­badgerdocs.dolphindb.cn/­en/­help200/­index.htmlfirebase.google.com/­docs/­databasecloud.google.com/­bigtable/­docs
DeveloperAmazonDGraph LabsDolphinDB, IncGoogle infoacquired by Google 2014Google
Initial release20172017201820122015
Current releasev2.00.4, January 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree community version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++
Server operating systemshostedBSD
Linux
OS X
Solaris
Windows
Linux
Windows
hostedhosted
Data schemeschema-freeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyesyesno
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.nonononono
Secondary indexesnonoyesyesno
SQL infoSupport of SQLnonoSQL-like query languagenono
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
GoC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
Java
JavaScript
Objective-C
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoyeslimited functionality with using 'rules'no
TriggersnononoCallbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodesnonenonehorizontal partitioningSharding
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.noneyesInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyes infoRelationships in graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyesyesAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noAdministrators, Users, Groupsyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon NeptuneBadgerDolphinDBFirebase Realtime DatabaseGoogle Cloud Bigtable
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