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DBMS > Amazon Neptune vs. Apache IoTDB vs. Graph Engine vs. HBase vs. Sqrrl

System Properties Comparison Amazon Neptune vs. Apache IoTDB vs. Graph Engine vs. HBase vs. Sqrrl

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHBase  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 cloudAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineWide-column store based on Apache Hadoop and on concepts of BigTableAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelGraph DBMS
RDF store
Time Series DBMSGraph DBMS
Key-value store
Wide column storeDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#112  Overall
#9  Graph DBMS
#5  RDF stores
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score0.62
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score31.25
Rank#26  Overall
#2  Wide column stores
Websiteaws.amazon.com/­neptuneiotdb.apache.orgwww.graphengine.iohbase.apache.orgsqrrl.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualhbase.apache.org/­book.html
DeveloperAmazonApache Software FoundationMicrosoftApache Software Foundation infoApache top-level project, originally developed by PowersetAmazon infooriginally Sqrrl Data, Inc.
Initial release20172018201020082012
Current release1.1.0, April 20232.3.4, January 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoMIT LicenseOpen Source infoApache version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava.NET and CJavaJava
Server operating systemshostedAll OS with a Java VM (>= 1.8).NETLinux
Unix
Windows infousing Cygwin
Linux
Data schemeschema-freeyesyesschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyesyesyesoptions to bring your own types, AVROyes
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.nononono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoSQL-like query languagenonono
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
Native API
RESTful HTTP APIJava API
RESTful HTTP API
Thrift
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
C#
C++
F#
Visual Basic
C
C#
C++
Groovy
Java
PHP
Python
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoyesyesyes infoCoprocessors in Javano
Triggersnoyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningShardingSharding 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.selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
selectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparkyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityyes infoRelationships in graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoSingle row ACID (across millions of columns)Atomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Amazon NeptuneApache IoTDBGraph Engine infoformer name: TrinityHBaseSqrrl
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