DBMS > Google Cloud Bigtable vs. H2 vs. MongoDB vs. YugabyteDB

System Properties Comparison Google Cloud Bigtable vs. H2 vs. MongoDB vs. YugabyteDB

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Editorial information provided by DB-Engines

Name

Description

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

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

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Key-value store
Wide column store

Relational DBMS

Document store

Relational DBMS

Secondary database models

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

Document store
Wide column store

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

Score	3.58
Rank	#92	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	423.96
Rank	#5	Overall
	#1	Document stores

Score	3.11
Rank	#99	Overall
	#51	Relational DBMS

Website

cloud.google.com/bigtable

www.h2database.com

www.mongodb.com

www.yugabyte.com

Technical documentation

cloud.google.com/bigtable/docs

www.h2database.com/html/main.html

www.mongodb.com/docs/manual

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Google

Thomas Mueller

MongoDB, Inc

Yugabyte Inc.

Initial release

2015

2005

2009

2017

Current release

2.2.220, July 2023

6.0.7, June 2023

2.19, September 2023

License

Commercial or Open Source

commercial

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

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.

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.

YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.

Implementation language

Java

C++

C and C++

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux
OS X

Data scheme

schema-free

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.

depending on used data model

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

SQL

Support of SQL

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes, PostgreSQL compatible

APIs and other access methods

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

JDBC
ODBC

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

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

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
Ruby
Rust
Scala

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

JavaScript

yes

sql, plpgsql, C

Triggers

yes

in MongoDB Atlas only

yes

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.

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

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

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-row operations

ACID

Multi-document ACID Transactions with snapshot isolation

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

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

based on RocksDB

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 Google Cloud Identity and Access Management (IAM)

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...
» more

YugabyteDB is an open source distributed SQL database for cloud native transactional...
» more

Competitive advantages

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

PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more

Typical application scenarios

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

Systems of record and engagement for cloud native applications that require resilience,...
» 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

2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more

Licensing and pricing models

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

Apache 2.0 license for the database
» more

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