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DBMS > Amazon Neptune vs. Citus vs. HugeGraph vs. InfinityDB vs. LevelDB

System Properties Comparison Amazon Neptune vs. Citus vs. HugeGraph vs. InfinityDB vs. LevelDB

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCitus  Xexclude from comparisonHugeGraph  Xexclude from comparisonInfinityDB  Xexclude from comparisonLevelDB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA fast-speed and highly-scalable Graph DBMSA Java embedded Key-Value Store which extends the Java Map interfaceEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string values
Primary database modelGraph DBMS
RDF store
Relational DBMSGraph DBMSKey-value storeKey-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score0.08
Rank#365  Overall
#55  Key-value stores
Score2.25
Rank#115  Overall
#19  Key-value stores
Websiteaws.amazon.com/­neptunewww.citusdata.comgithub.com/­hugegraph
hugegraph.apache.org
boilerbay.comgithub.com/­google/­leveldb
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.citusdata.comhugegraph.apache.org/­docsboilerbay.com/­infinitydb/­manualgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperAmazonBaiduBoiler Bay Inc.Google
Initial release20172010201820022011
Current release8.1, December 20180.94.01.23, February 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2.0commercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaJavaC++
Server operating systemshostedLinuxLinux
macOS
Unix
All OS with a Java VMIllumos
Linux
OS X
Windows
Data schemeschema-freeyesyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysno
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.noyes infospecific XML type available, but no XML query functionalitynonono
Secondary indexesnoyesyes infoalso supports composite index and range indexno infomanual creation possible, using inversions based on multi-value capabilityno
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsnonono
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP API
TinkerPop Gremlin
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Groovy
Java
Python
JavaC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.asynchronous Gremlin script jobsnono
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes infodepending on used storage backend, e.g. Cassandra and HBasenonenone
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.Source-replica replication infoother methods possible by using 3rd party extensionsyes infodepending on used storage backend, e.g. Cassandra and HBasenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonovia hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesyes infoedges in graphno infomanual creation possible, using inversions based on multi-value capabilityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes infowith automatic compression on writes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardUsers, roles and permissionsnono

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More resources
Amazon NeptuneCitusHugeGraphInfinityDBLevelDB
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