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DBMS > Amazon Neptune vs. DolphinDB vs. Microsoft Azure Cosmos DB vs. Sqrrl

System Properties Comparison Amazon Neptune vs. DolphinDB vs. Microsoft Azure Cosmos DB vs. Sqrrl

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDolphinDB  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
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.Globally distributed, horizontally scalable, multi-model database serviceAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelGraph DBMS
RDF store
Time Series DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Document store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsRelational DBMSSpatial 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
Score30.39
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Websiteaws.amazon.com/­neptunewww.dolphindb.comazure.microsoft.com/­services/­cosmos-dbsqrrl.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.dolphindb.cn/­en/­help200/­index.htmllearn.microsoft.com/­azure/­cosmos-db
DeveloperAmazonDolphinDB, IncMicrosoftAmazon infooriginally Sqrrl Data, Inc.
Initial release2017201820142012
Current releasev2.00.4, January 2022
License infoCommercial or Open Sourcecommercialcommercial infofree community version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemshostedLinux
Windows
hostedLinux
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infoJSON typesyes
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.nono
Secondary indexesnoyesyes infoAll properties auto-indexed by defaultyes
SQL infoSupport of SQLnoSQL-like query languageSQL-like query languageno
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
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoyesJavaScriptno
TriggersnonoJavaScriptno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningSharding infoImplicit feature of the cloud serviceSharding infomaking use of Hadoop
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.yesyes infoImplicit feature of the cloud serviceselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyeswith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*yes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityyes infoRelationships in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesMulti-item ACID transactions with snapshot isolation within a partitionAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Administrators, Users, GroupsAccess rights can be defined down to the item levelCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Amazon NeptuneDolphinDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSqrrl
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