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DBMS > Amazon DocumentDB vs. etcd vs. HBase vs. HEAVY.AI vs. Heroic

System Properties Comparison Amazon DocumentDB vs. etcd vs. HBase vs. HEAVY.AI vs. Heroic

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonetcd  Xexclude from comparisonHBase  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonHeroic  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA distributed reliable key-value storeWide-column store based on Apache Hadoop and on concepts of BigTableA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch
Primary database modelDocument storeKey-value storeWide column storeRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score7.64
Rank#54  Overall
#5  Key-value stores
Score31.25
Rank#26  Overall
#2  Wide column stores
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score0.57
Rank#250  Overall
#21  Time Series DBMS
Websiteaws.amazon.com/­documentdbetcd.io
github.com/­etcd-io/­etcd
hbase.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
github.com/­spotify/­heroic
Technical documentationaws.amazon.com/­documentdb/­resourcesetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
hbase.apache.org/­book.htmldocs.heavy.aispotify.github.io/­heroic
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetHEAVY.AI, Inc.Spotify
Initial release2019200820162014
Current release3.4, August 20192.3.4, January 20215.10, January 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache version 2Open Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaC++ and CUDAJava
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
Linux
Unix
Windows infousing Cygwin
Linux
Data schemeschema-freeschema-freeschema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateyesnooptions to bring your own types, AVROyesyes
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.nonononono
Secondary indexesyesnononoyes infovia Elasticsearch
SQL infoSupport of SQLnononoyesno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC
JSON over HTTP
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
Vega
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C
C#
C++
Groovy
Java
PHP
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javanono
Triggersnoyes, watching key changesyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication
Source-replica replication
Multi-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoSingle row ACID (across millions of columns)nono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlAccess rights for users and rolesnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBetcdHBaseHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Heroic
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