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DBMS > Amazon Neptune vs. HarperDB vs. HugeGraph vs. MarkLogic

System Properties Comparison Amazon Neptune vs. HarperDB vs. HugeGraph vs. MarkLogic

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonHarperDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonMarkLogic  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.A fast-speed and highly-scalable Graph DBMSOperational and transactional Enterprise NoSQL database
Primary database modelGraph DBMS
RDF store
Document storeGraph DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.60
Rank#244  Overall
#38  Document stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Websiteaws.amazon.com/­neptunewww.harperdb.iogithub.com/­hugegraph
hugegraph.apache.org
www.progress.com/­marklogic
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.harperdb.io/­docshugegraph.apache.org/­docswww.progress.com/­marklogic/­documentation
DeveloperAmazonHarperDBBaiduMarkLogic Corp.
Initial release2017201720182001
Current release3.1, August 20210.911.0, December 2022
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoApache Version 2.0commercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageNode.jsJavaC++
Server operating systemshostedLinux
OS X
Linux
macOS
Unix
Linux
OS X
Windows
Data schemeschema-freedynamic schemayesschema-free infoSchema can be enforced
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyes
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.nononoyes
Secondary indexesnoyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLnoSQL-like data manipulation statementsnoyes infoSQL92
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Java API
RESTful HTTP API
TinkerPop Gremlin
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Groovy
Java
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1asynchronous Gremlin script jobsyes infovia XQuery or JavaScript
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneA table resides as a whole on one (or more) nodes in a clusteryes infodepending on used storage backend, e.g. Cassandra and HBaseSharding
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.yes infothe nodes on which a table resides can be definedyes infodepending on used storage backend, e.g. Cassandra and HBaseyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonovia hugegraph-sparkyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACIDACID infocan act as a resource manager in an XA/JTA transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes, with Range Indexes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users and rolesUsers, roles and permissionsRole-based access control at the document and subdocument levels

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More resources
Amazon NeptuneHarperDBHugeGraphMarkLogic
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