DBMS > Amazon CloudSearch vs. MongoDB vs. Raima Database Manager vs. Solr vs. Vertica

System Properties Comparison Amazon CloudSearch vs. MongoDB vs. Raima Database Manager vs. Solr vs. Vertica

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

RDBMS with a small footprint, either embedded into an application or used as a database server

A widely used distributed, scalable search engine based on Apache Lucene

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Search engine

Document store

Relational DBMS
Time Series DBMS

Search engine

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	0.46
Rank	#259	Overall
	#120	Relational DBMS
	#22	Time Series DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

aws.amazon.com/cloudsearch

Technical documentation

docs.aws.amazon.com/cloudsearch

www.mongodb.com/docs/manual

docs.raima.com

solr.apache.org/resources.html

vertica.com/documentation

Developer

Amazon

MongoDB, Inc

Raima Inc.

Apache Software Foundation

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2012

2009

1984

2006

2005

Current release

6.0.7, June 2023

15, June 2021

9.6.0, April 2024

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

commercial

Open Source

Apache Version 2

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Android
HP-UX
Integrity RTOS
iOS
Linux
OS X
QNX
Solaris
VxWorks
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux

Data scheme

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes

Dynamic Fields enables on-the-fly addition of new fields

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

yes

supports customizable data types and automatic typing

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.

Exporting/Importing of XML structures possible

yes

Secondary indexes

yes

all search fields are automatically indexed

yes

All search fields are automatically indexed

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

Solr Parallel SQL Interface

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

ADO.NET
JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

.Net
C
C++
Objective-C
PL/SQL

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

JavaScript

yes

based on the ANSI/ISO SQL Persistent Stored Modules (PSM) specification

Java plugins

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

in MongoDB Atlas only

yes

User configurable commands triggered on index changes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

horizontal partitioning

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

Source-replica replication

yes

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Multi-document ACID Transactions with snapshot isolation

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

authentication via encrypted signatures

Access rights for users and roles

yes

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Raima Database Manager (RDM) is an embedded time-series database optimized to run...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Decreased time-to-market Industry-standard interfaces & tools for making your job...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Typical use cases include: Internet of Things (IoT) Embedded In-Memory Database Time-Series...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Infor, ABB, The Boeing Company, BAE Systems, Dow Jones, Dun & Bradstreet, Fujitsu,...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Over 30 000 applications developers worldwide have field-tested RDM products More...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

Just as the technical aspects of Raima Database Manager are flexible, so are the...
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Cost-based models and subscription-based models are both available. One license is...
» more

News

Raima Unveils RaimaDB 16.0: Elevating Database Performance and User Experience
29 February 2024

Raima Announces Release of Raima Database Manager (RDM) v15, a Powerful Embedded Time Series Database
10 June 2021

Raima Announces Release of Raima Database Manager (RDM) v14.2, a Powerful IoT Edge Embedded Database
8 October 2020

Raima Joins BlackBerry QNX Channel Partner Program to Deliver Safety-Critical and Secure Software Solutions
1 October 2020

Raima Expands Their Reseller Network in Asia
19 May 2020

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.