DBMS > Google BigQuery vs. Greenplum vs. Riak TS vs. SurrealDB

System Properties Comparison Google BigQuery vs. Greenplum vs. Riak TS vs. SurrealDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

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.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Relational DBMS

Time Series DBMS

Document store
Graph DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

cloud.google.com/bigquery

greenplum.org

surrealdb.com

Technical documentation

cloud.google.com/bigquery/docs

docs.greenplum.org

www.tiot.jp/riak-docs/riak/ts/latest

surrealdb.com/docs

Developer

Google

Pivotal Software Inc.

Open Source, formerly Basho Technologies

SurrealDB Ltd

Initial release

2010

2005

2015

2022

Current release

7.0.0, September 2023

3.0.0, September 2022

v1.5.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

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.

Implementation language

Erlang

Rust

Server operating systems

hosted

Linux

Linux
OS X

Linux
macOS
Windows

Data scheme

yes

schema-free

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.

yes

since Version 4.2

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

yes, limited

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

HTTP API
Native Erlang Interface

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
Java
Perl
Python
R

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

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

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.