DBMS > Google BigQuery vs. HyperSQL vs. Riak TS vs. StarRocks

System Properties Comparison Google BigQuery vs. HyperSQL vs. Riak TS vs. StarRocks

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Website

cloud.google.com/bigquery

hsqldb.org

www.starrocks.io

Technical documentation

cloud.google.com/bigquery/docs

hsqldb.org/web/hsqlDocsFrame.html

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

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Google

Open Source, formerly Basho Technologies

The Linux Foundation

since Feb 2023

Initial release

2010

2001

2015

2020

Current release

2.7.2, June 2023

3.0.0, September 2022

2.5.3, March 2023

License

Commercial or Open Source

commercial

Open Source

based on BSD license

Open Source

Apache Version 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.

Implementation language

Java

Erlang

C++, Java

Server operating systems

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
OS X

Linux

Data scheme

yes

schema-free

yes

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

restricted

yes

SQL

Support of SQL

yes

yes, limited

yes

APIs and other access methods

RESTful HTTP/JSON API

HTTP API

JDBC via HTTP
JDBC
ODBC

HTTP API
Native Erlang Interface

JDBC
MySQL protocol

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC
Java

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

Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java, SQL

Erlang

user defined functions

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Immediate 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.

yes

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

Role based access control and fine grained access rights

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