DBMS > Amazon DocumentDB vs. HEAVY.AI vs. KeyDB vs. OpenSearch

System Properties Comparison Amazon DocumentDB vs. HEAVY.AI vs. KeyDB vs. OpenSearch

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Primary database model

Secondary database models

Spatial DBMS

Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	16.36
Rank	#37	Overall
	#4	Search engines

Website

aws.amazon.com/documentdb

github.com/heavyai/heavydb
www.heavy.ai

github.com/Snapchat/KeyDB
keydb.dev

github.com/opensearch-project
opensearch.org

Technical documentation

aws.amazon.com/documentdb/resources

docs.heavy.ai

docs.keydb.dev

opensearch.org/docs/latest

Developer

HEAVY.AI, Inc.

EQ Alpha Technology Ltd.

Amazon Web Services

Initial release

2019

2016

2019

2021

Current release

5.10, January 2022

2.5.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

BSD-3

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

C++ and CUDA

C++

Java

Server operating systems

hosted

Linux

All OS with a Java VM

Data scheme

schema-free

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

by using the Redis Search module

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC
Thrift
Vega

Proprietary protocol

RESP - REdis Serialization Protoco

Java API
RESTful HTTP/JSON API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Multi-source replication

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-document operations

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

simple password-based access control and ACL

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
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Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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