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DBMS > Amazon DocumentDB vs. Apache Impala vs. Google Cloud Bigtable vs. Heroic

System Properties Comparison Amazon DocumentDB vs. Apache Impala vs. Google Cloud Bigtable vs. Heroic

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHeroic  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAnalytic DBMS for HadoopGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch
Primary database modelDocument storeRelational DBMSKey-value store
Wide column store
Time Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Websiteaws.amazon.com/­documentdbimpala.apache.orgcloud.google.com/­bigtablegithub.com/­spotify/­heroic
Technical documentationaws.amazon.com/­documentdb/­resourcesimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docsspotify.github.io/­heroic
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleSpotify
Initial release2019201320152014
Current release4.1.0, June 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemshostedLinuxhosted
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesyesnoyes infovia Elasticsearch
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon DocumentDBApache ImpalaGoogle Cloud BigtableHeroic
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