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DBMS > Amazon Neptune vs. Google Cloud Bigtable vs. Hive vs. HugeGraph

System Properties Comparison Amazon Neptune vs. Google Cloud Bigtable vs. Hive vs. HugeGraph

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHive  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.data warehouse software for querying and managing large distributed datasets, built on HadoopA fast-speed and highly-scalable Graph DBMS
Primary database modelGraph DBMS
RDF store
Key-value store
Wide column store
Relational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#112  Overall
#9  Graph DBMS
#5  RDF stores
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score0.15
Rank#339  Overall
#33  Graph DBMS
Websiteaws.amazon.com/­neptunecloud.google.com/­bigtablehive.apache.orggithub.com/­hugegraph
hugegraph.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcescloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Homehugegraph.apache.org/­docs
DeveloperAmazonGoogleApache Software Foundation infoinitially developed by FacebookBaidu
Initial release2017201520122018
Current release3.1.3, April 20220.9
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemshostedhostedAll OS with a Java VMLinux
macOS
Unix
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonono
Secondary indexesnonoyesyes infoalso supports composite index and range index
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
Groovy
Java
Python
Server-side scripts infoStored proceduresnonoyes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobs
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes 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.Internal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReducevia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACID
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.noyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesUsers, roles and permissions

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More resources
Amazon NeptuneGoogle Cloud BigtableHiveHugeGraph
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