DBMS > Apache IoTDB vs. GeoSpock vs. Google Cloud Bigtable vs. MongoDB vs. TiDB

System Properties Comparison Apache IoTDB vs. GeoSpock vs. Google Cloud Bigtable vs. MongoDB vs. TiDB

Editorial information provided by DB-Engines

Name

Description

A lightweight IoT native database management system deployable on the device and syncing the collected data with the cloud and integrated with Hadoop and Spark

Spatial and temporal data processing engine for extreme data scale

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

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

TiDB is an open source distributed Hybrid Transactional/Analytical Processing (HTAP) database that supports MySQL and Spark SQL syntaxes.

Primary database model

Time Series DBMS

Relational DBMS

Key-value store
Wide column store

Document store

Relational DBMS

Secondary database models

Time Series DBMS

Spatial DBMS
Search engine

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

Time Series Collections introduced in Release 5.0

Document store

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

Score	0.42
Rank	#253	Overall
	#20	Time Series DBMS

Score	0.16
Rank	#299	Overall
	#138	Relational DBMS

Score	4.26
Rank	#86	Overall
	#14	Key-value stores
	#6	Wide column stores

Score	478.24
Rank	#5	Overall
	#1	Document stores

Score	3.54
Rank	#93	Overall
	#49	Relational DBMS

Website

iotdb.apache.org

geospock.com

cloud.google.com/bigtable

www.mongodb.com

pingcap.com

Technical documentation

docs.geospock.com/Content/Home.htm

cloud.google.com/bigtable/docs

docs.mongodb.com/manual

docs.pingcap.com/tidb/stable

Developer

Apache Software Foundation

GeoSpock

Google

MongoDB, Inc

PingCAP, Inc.

Initial release

2018

2015

2009

2016

Current release

2.0, September 2019

5.0.6, January 2022

5.0.1, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

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

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.

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TiDB Cloud: Fully-managed TiDB Service. Bring everything great about TiDB to the cloud.

Implementation language

Java

Java, Javascript

C++

Go, Rust

Server operating systems

All OS with a Java VM (>= 1.8)

hosted

Linux
OS X
Solaris
Windows

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

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

temporal, categorical

yes

SQL

Support of SQL

SQL-like query language

ANSI SQL for query only (using Presto)

Read-only SQL queries via the MongoDB Connector for BI

yes

APIs and other access methods

JDBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

proprietary protocol using JSON

JDBC
ODBC
Proprietary protocol

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
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
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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

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 (by key range)

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

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

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

with TiSpark Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency with synchronizing with the cloud

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

currently only supported in syntax

Transaction concepts

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

Atomic single-row operations

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

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 can be defined per table

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

Users with fine-grained authorization concept. No user groups or roles.

More information provided by the system vendor

Specific characteristics

MongoDB’s application data platform provides developers a unified interface to power...
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TiDB is an open-source NewSQL database built by PingCAP. TiDB supports Hybrid Transactional...
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Competitive advantages

The MongoDB platform can be used by developers building transactional, operational,...
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In the current database landscape, infrastructure engineers often have to use one...
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Typical application scenarios

Internet of Things and Time Series (Bosch, Jaguar Land Rover) Mobile (The Weather...
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TiDB is designed to support both OLTP and OLAP scenarios. You can use TiDB , the...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Shopee (E-commerce) BookMyShow.com (E-commerce) Yiguo.com (E-commerce) JD Cloud &...
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Market metrics

200+ million downloads, over 1.5M Atlas database clusters under management handling...
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25K+ GitHub Stars for TiDB, and 8K+ GitHub Stars for TiKV 1.6K+ members in TiDB Community...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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Open Source Apache 2.0 with either commercial licensing or fully-hosted DB-as-a-service...
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News

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7 December 2021

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30 November 2021

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24 November 2021

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