DBMS > Google Cloud Bigtable vs. GreptimeDB vs. MongoDB vs. TypeDB vs. Yaacomo

System Properties Comparison Google Cloud Bigtable vs. GreptimeDB vs. MongoDB vs. TypeDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

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.

An open source Time Series DBMS built for increased scalability, high performance and efficiency

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

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Key-value store
Wide column store

Time Series DBMS

Document store

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Relational 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

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

cloud.google.com/bigtable

greptime.com

www.mongodb.com

typedb.com

yaacomo.com

Technical documentation

cloud.google.com/bigtable/docs

docs.greptime.com

www.mongodb.com/docs/manual

typedb.com/docs

Developer

Google

Greptime Inc.

MongoDB, Inc

Vaticle

Q2WEB GmbH

Initial release

2015

2022

2009

2016

2009

Current release

6.0.7, June 2023

2.26.3, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

GPL Version 3, commercial licenses available

commercial

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

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Implementation language

Rust

C++

Java

Server operating systems

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Android
Linux
Windows

Data scheme

schema-free

schema-free, schema definition possible

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

SQL

Support of SQL

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

APIs and other access methods

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

gRPC
HTTP API
JDBC

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

JDBC
ODBC

Supported programming languages

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

C++
Erlang
Go
Java
JavaScript

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

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

Python

JavaScript

Triggers

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

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

by using Cassandra

horizontal partitioning

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

Multi-source replication

by using Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

by using Apache Kafka and Apache Zookeeper

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

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

substituted by the relationship feature

yes

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

yes

User concepts

Access control

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

Simple rights management via user accounts

Access rights for users and roles

yes

at REST API level; other APIs in progress

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
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MongoDB provides an integrated suite of cloud database and data services to accelerate...
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TypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
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Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
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Built around the flexible document data model and unified API, MongoDB is a developer...
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TypeDB provides a new level of expressivity, extensibility, interoperability, and...
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Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
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AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Life sciences : TypeDB makes working with biological data much easier and accelerates...
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Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
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ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
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Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
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MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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Apache f or language drivers, and AGPL and Commercial for the database server. The...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.