DBMS > Hive vs. Ingres vs. MongoDB vs. Prometheus vs. TDengine

System Properties Comparison Hive vs. Ingres vs. MongoDB vs. Prometheus vs. TDengine

Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Well established RDBMS

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

Open-source Time Series DBMS and monitoring system

Time Series DBMS and big data platform

Primary database model

Relational DBMS

Document store

Time Series DBMS

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

Relational DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

hive.apache.org

www.actian.com/databases/ingres

www.mongodb.com

prometheus.io

github.com/taosdata/TDengine
tdengine.com

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

docs.actian.com/ingres

www.mongodb.com/docs/manual

prometheus.io/docs

docs.tdengine.com

Developer

Apache Software Foundation

initially developed by Facebook

Actian Corporation

MongoDB, Inc

TDEngine, previously Taos Data

Initial release

2012

1974

originally developed at University Berkely in early 1970s

2009

2015

2019

Current release

3.1.3, April 2022

11.2, May 2022

6.0.7, June 2023

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache Version 2

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 2.0

Open Source

AGPL V3, also commercial editions available

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
OS X
Solaris
Windows

Linux
Windows

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

Typing

predefined data types such as float or date

yes

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

Numeric data only

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.

but tools for importing/exporting data from/to XML-files available

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC
ODBC
Thrift

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

RESTful HTTP/JSON API

JDBC
RESTful HTTP API

Supported programming languages

C++
Java
PHP
Python

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++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

JavaScript

Triggers

yes

in MongoDB Atlas only

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Ingres Replicator

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

yes

by Federation

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

Eventual Consistency

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

none

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

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

User concepts

Access control

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

Access rights for users and roles

yes

More information provided by the system vendor

Specific characteristics

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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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TDengine OSS is an open source, cloud native time series database. It includes built-in...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.