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

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

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDolphinDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHawkular Metrics  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudDolphinDB 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.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database modelGraph DBMS
RDF store
Time Series DBMSDocument storeKey-value store
Wide column store
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.82
Rank#109  Overall
#9  Graph DBMS
#5  RDF stores
Score4.14
Rank#85  Overall
#6  Time Series DBMS
Score15.07
Rank#38  Overall
#6  Document stores
Score3.86
Rank#90  Overall
#13  Key-value stores
#7  Wide column stores
Score0.07
Rank#366  Overall
#38  Time Series DBMS
Websiteaws.amazon.com/­neptunewww.dolphindb.comfirebase.google.com/­products/­realtime-databasecloud.google.com/­bigtablewww.hawkular.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.dolphindb.cn/­en/­help200/­index.htmlfirebase.google.com/­docs/­databasecloud.google.com/­bigtable/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperAmazonDolphinDB, IncGoogle infoacquired by Google 2014GoogleCommunity supported by Red Hat
Initial release20172018201220152014
Current releasev2.00.4, January 2022
License infoCommercial or Open Sourcecommercialcommercial infofree community version availablecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemshostedLinux
Windows
hostedhostedLinux
OS X
Windows
Data schemeschema-freeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesnoyesyesnono
SQL infoSupport of SQLnoSQL-like query languagenonono
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)
HTTP REST
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
Java
JavaScript
Objective-C
C#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyeslimited functionality with using 'rules'nono
TriggersnonoCallbacks are triggered when data changesnoyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningShardingSharding infobased on Cassandra
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.yesInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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)Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integrityyes infoRelationships in graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesyesAtomic single-row operationsno
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.yesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Administrators, Users, Groupsyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Amazon NeptuneDolphinDBFirebase Realtime DatabaseGoogle Cloud BigtableHawkular Metrics
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