DBMS > Datastax Enterprise vs. Firebase Realtime Database vs. MongoDB vs. OpenSearch vs. TimesTen

System Properties Comparison Datastax Enterprise vs. Firebase Realtime Database vs. MongoDB vs. OpenSearch vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

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

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

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Vector DBMS

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

Score	5.93
Rank	#56	Overall
	#4	Wide column stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.datastax.com/products/datastax-enterprise

firebase.google.com/products/realtime-database

www.mongodb.com

github.com/opensearch-project
opensearch.org

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.datastax.com

firebase.google.com/docs/database

www.mongodb.com/docs/manual

opensearch.org/docs/latest

docs.oracle.com/database/timesten-18.1

Developer

DataStax

Google

acquired by Google 2014

MongoDB, Inc

Amazon Web Services

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2011

2012

2009

2021

1998

Current release

6.8, April 2020

6.0.7, June 2023

2.5.0, January 2023

11 Release 2 (11.2.2.8.0)

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.

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

MongoDB Flex @ STACKIT offers managed MongoDB Instances with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

Aiven for OpenSearch: Fully managed open source search and analytics suite. Out-of-the-box integrations get you up and running in a couple of clicks.
STACKIT OpenSearch offers OpenSearch in a managed version in enterprise grade, 100% GDPR-compliant, for a wide range of applications like analytics, website search, offering scalability and fast data access.

Implementation language

Java

C++

Java

Server operating systems

Linux
OS X

hosted

Linux
OS X
Solaris
Windows

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

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.

schema-free

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

yes

Typing

predefined data types such as float or date

yes

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

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements (CQL); Spark SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

SQL-like query language

yes

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

Android
iOS
JavaScript API
RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Java API
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
JavaScript
Objective-C

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

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

limited functionality with using 'rules'

JavaScript

yes

PL/SQL

Triggers

yes

Callbacks are triggered when data changes

yes

in MongoDB Atlas only

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

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.

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware, advanced replication for edge computing

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

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Eventual Consistency

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

Immediate Consistency or Eventual Consistency depending on configuration

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

Atomicity and isolation are supported for single operations

yes

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

by means of logfiles and checkpoints

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

Access rights for users can be defined per object

yes, based on authentication and database rules

Access rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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MongoDB provides an integrated suite of cloud database and data services to accelerate...
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OpenSearch is a highly scalable and extensible open-source software suite for search,...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Built around the flexible document data model and unified API, MongoDB is a developer...
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Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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The OpenSearch platform is used across a broad range of search , analytics, and observability...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

Annual subscription
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MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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The OpenSearch Project offers open source software licensed under Apache License...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.