DBMS > Apache Impala vs. Greenplum vs. H2 vs. MongoDB vs. TDengine

System Properties Comparison Apache Impala vs. Greenplum vs. H2 vs. MongoDB vs. TDengine

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Time Series DBMS and big data platform

Primary database model

Relational DBMS

Document store

Time Series DBMS

Secondary database models

Document store

Document store
Spatial DBMS

Spatial 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

Relational DBMS

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	7.71
Rank	#46	Overall
	#29	Relational DBMS

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	410.24
Rank	#5	Overall
	#1	Document stores

Score	2.48
Rank	#107	Overall
	#9	Time Series DBMS

Website

github.com/taosdata/TDengine
tdengine.com

Technical documentation

impala.apache.org/impala-docs.html

docs.greenplum.org

www.h2database.com/html/main.html

www.mongodb.com/docs/manual

docs.tdengine.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Pivotal Software Inc.

Thomas Mueller

MongoDB, Inc

TDEngine, previously Taos Data

Initial release

2013

2005

2009

2019

Current release

4.1.0, June 2022

7.0.0, September 2023

2.2.220, July 2023

7.0.5, January 2024

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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

AGPL V3, also commercial editions available

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

C++

Java

C++

Server operating systems

Linux

All OS with a Java VM

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

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.

yes

since Version 4.2

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

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

JDBC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
Java
Perl
Python
R

Java

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

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

Java Stored Procedures and User-Defined Functions

JavaScript

Triggers

yes

in MongoDB Atlas only

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-Source deployments with MongoDB Atlas Global Clusters
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

Eventual Consistency

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

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

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

Access rights for users and roles

yes

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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TDengine™ is a time-series database designed to help traditional industries overcome...
» more

Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
» more

High Performance at Any Scale: With its distributed scalable architecture that grows...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more

TDengine is purpose-built for Industry 4.0 and the Industrial IoT (IIoT) and particularly...
» more

Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

TDengine has garnered over 23,000 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

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

TDengine OSS is free, open-source software released under the AGPLv3. TDengine Enterprise...
» more

News

Optimize Data Consolidation for Multi-Site Renewable Energy Operations
9 September 2024

Connect Power BI to TDengine
6 September 2024

Using Streams and Subscriptions for Alerting
5 September 2024

Solar Panel Monitoring: OPC UA Ingestion
2 September 2024

Time-Series Databases: A Game Changer for the Renewable Energy Industry
30 August 2024

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