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DBMS > Amazon DocumentDB vs. Amazon Neptune vs. Drizzle vs. Heroic vs. Kinetica

System Properties Comparison Amazon DocumentDB vs. Amazon Neptune vs. Drizzle vs. Heroic vs. Kinetica

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonDrizzle  Xexclude from comparisonHeroic  Xexclude from comparisonKinetica  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceFast, reliable graph database built for the cloudMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully vectorized database across both GPUs and CPUs
Primary database modelDocument storeGraph DBMS
RDF store
Relational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websiteaws.amazon.com/­documentdbaws.amazon.com/­neptunegithub.com/­spotify/­heroicwww.kinetica.com
Technical documentationaws.amazon.com/­documentdb/­resourcesaws.amazon.com/­neptune/­developer-resourcesspotify.github.io/­heroicdocs.kinetica.com
DeveloperAmazonDrizzle project, originally started by Brian AkerSpotifyKinetica
Initial release20192017200820142012
Current release7.2.4, September 20127.1, August 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGNU GPLOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC, C++
Server operating systemshostedhostedFreeBSD
Linux
OS X
Linux
Data schemeschema-freeschema-freeyesschema-freeyes
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.nononono
Secondary indexesyesnoyesyes infovia Elasticsearchyes
SQL infoSupport of SQLnonoyes infowith proprietary extensionsnoSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBCHQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C++
Java
PHP
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonononouser defined functions
Triggersnonono infohooks for callbacks inside the server can be used.noyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-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.Multi-source replication
Source-replica replication
yesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infoRelationships in graphsyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Pluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and roles on table level

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More resources
Amazon DocumentDBAmazon NeptuneDrizzleHeroicKinetica
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