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DBMS > Amazon Neptune vs. BigObject vs. Datomic vs. DuckDB vs. HugeGraph

System Properties Comparison Amazon Neptune vs. BigObject vs. Datomic vs. DuckDB vs. HugeGraph

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonBigObject  Xexclude from comparisonDatomic  Xexclude from comparisonDuckDB  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAnalytic DBMS for real-time computations and queriesDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAn embeddable, in-process, column-oriented SQL OLAP RDBMSA fast-speed and highly-scalable Graph DBMS
Primary database modelGraph DBMS
RDF store
Relational DBMS infoa hierachical model (tree) can be imposedRelational DBMSRelational DBMSGraph 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
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score4.57
Rank#74  Overall
#40  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websiteaws.amazon.com/­neptunebigobject.iowww.datomic.comduckdb.orggithub.com/­hugegraph
hugegraph.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.bigobject.iodocs.datomic.comduckdb.org/­docshugegraph.apache.org/­docs
DeveloperAmazonBigObject, Inc.CognitectBaidu
Initial release20172015201220182018
Current release1.0.6735, June 20230.10, February 20240.9
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availablecommercial infolimited edition freeOpen Source infoMIT LicenseOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++Java
Server operating systemshostedLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
All OS with a Java VMserver-lessLinux
macOS
Unix
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesnoyesyesyesyes infoalso supports composite index and range index
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoyesno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
fluentd
ODBC
RESTful HTTP API
RESTful HTTP APIArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Clojure
Java
C
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
Groovy
Java
Python
Server-side scripts infoStored proceduresnoLuayes infoTransaction Functionsnoasynchronous Gremlin script jobs
TriggersnonoBy using transaction functionsnono
Partitioning methods infoMethods for storing different data on different nodesnonenonenone infoBut extensive use of caching in the application peersnoneyes infodepending on used storage backend, e.g. Cassandra and HBase
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.nonenone infoBut extensive use of caching in the application peersnoneyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononovia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infoautomatically between fact table and dimension tablesnonoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)nononoUsers, roles and permissions

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More resources
Amazon NeptuneBigObjectDatomicDuckDBHugeGraph
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