DBMS > Google BigQuery vs. IBM Cloudant vs. PlanetScale vs. TinkerGraph vs. YugabyteDB

System Properties Comparison Google BigQuery vs. IBM Cloudant vs. PlanetScale vs. TinkerGraph vs. YugabyteDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Database as a Service offering based on Apache CouchDB

Scalable, distributed, serverless MySQL database platform built on top of Vitess

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

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

Primary database model

Secondary database models

Document store
Spatial DBMS

Document store
Wide column store

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Score	2.91
Rank	#102	Overall
	#51	Relational DBMS

Website

cloud.google.com/bigquery

www.ibm.com/products/cloudant

planetscale.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

www.yugabyte.com

Technical documentation

cloud.google.com/bigquery/docs

cloud.ibm.com/docs/Cloudant

planetscale.com/docs

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

Developer

Google

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

PlanetScale

Yugabyte Inc.

Initial release

2010

2020

2009

2017

Current release

2.19, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

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

Erlang

Java

C and C++

Server operating systems

hosted

Docker
Linux
macOS

Linux
OS X

Data scheme

yes

schema-free

yes

schema-free

depending on used data model

Typing

predefined data types such as float or date

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

with proprietary extensions

yes, PostgreSQL compatible

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
MySQL protocol
ODBC

TinkerPop 3

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

Groovy
Java

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

View functions (Map-Reduce) in JavaScript

yes

proprietary syntax

yes

sql, plpgsql, C

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

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

Eventual Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

none

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Relationships in graphs

yes

Transaction concepts

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

Since BigQuery is designed for querying data

atomic operations within a document possible

ACID at shard level

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

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

optional

yes

based on RocksDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users can be defined per database

Users with fine-grained authorization concept

no user groups or roles

yes

More information provided by the system vendor

Specific characteristics

YugabyteDB is an open source distributed SQL database for cloud native transactional...
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Competitive advantages

PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
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Typical application scenarios

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

2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
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Licensing and pricing models

Apache 2.0 license for the database
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