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DBMS > Amazon Neptune vs. Apache IoTDB vs. Faircom DB vs. Heroic

System Properties Comparison Amazon Neptune vs. Apache IoTDB vs. Faircom DB vs. Heroic

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache IoTDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonHeroic  Xexclude from comparison
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 FlinkNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch
Primary database modelGraph DBMS
RDF store
Time Series DBMSKey-value store
Relational DBMS
Time Series 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
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Websiteaws.amazon.com/­neptuneiotdb.apache.orgwww.faircom.com/­products/­faircom-dbgithub.com/­spotify/­heroic
Technical documentationaws.amazon.com/­neptune/­developer-resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlspotify.github.io/­heroic
DeveloperAmazonApache Software FoundationFairCom CorporationSpotify
Initial release2017201819792014
Current release1.1.0, April 2023V12, November 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++Java
Server operating systemshostedAll OS with a Java VM (>= 1.8)AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Data schemeschema-freeyesschema free, schema optional, schema required, partial schema,schema-free
Typing infopredefined data types such as float or dateyesyesyes, ANSI SQL Types, JSON, typed binary structuresyes
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 indexesnoyesyesyes infovia Elasticsearch
SQL infoSupport of SQLnoSQL-like query languageyes, ANSI SQL with proprietary extensionsno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
Native API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Server-side scripts infoStored proceduresnoyesyes info.Net, JavaScript, C/C++no
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)File partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding
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 replicasyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnotunable from ACID to Eventually Consistentno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesYes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesFine grained access rights according to SQL-standard with additional protections for files

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More resources
Amazon NeptuneApache IoTDBFaircom DB infoformerly c-treeACEHeroic
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