DBMS > Amazon Neptune vs. Apache Impala vs. BoltDB vs. CouchDB vs. OpenSearch

System Properties Comparison Amazon Neptune vs. Apache Impala vs. BoltDB vs. CouchDB vs. OpenSearch

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Analytic DBMS for Hadoop

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

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

Primary database model

Secondary database models

Document store

Spatial DBMS

using the Geocouch extension

Vector DBMS

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

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	16.03
Rank	#37	Overall
	#4	Search engines

Website

aws.amazon.com/neptune

impala.apache.org

github.com/boltdb/bolt

couchdb.apache.org

github.com/opensearch-project
opensearch.org

Technical documentation

aws.amazon.com/neptune/developer-resources

impala.apache.org/impala-docs.html

docs.couchdb.org/en/stable

opensearch.org/docs/latest

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Amazon Web Services

Initial release

2017

2013

2005

2021

Current release

4.1.0, June 2022

3.3.3, December 2023

2.5.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

MIT License

Open Source

Apache version 2

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++

Erlang

Java

Server operating systems

hosted

Linux

BSD
Linux
OS X
Solaris
Windows

Android
BSD
Linux
OS X
Solaris
Windows

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

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

via views

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
ODBC

RESTful HTTP/JSON API

Java API
RESTful HTTP/JSON API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

View functions in JavaScript

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

improved architecture with release 2.0

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-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 factor

none

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

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

yes

Relationships in graphs

Transaction concepts

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

ACID

yes

atomic operations within a single document possible

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users can be defined per database

More information provided by the system vendor

Specific characteristics

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

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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