DBMS > Google BigQuery vs. HyperSQL vs. IRONdb vs. Riak KV vs. TerminusDB

System Properties Comparison Google BigQuery vs. HyperSQL vs. IRONdb vs. Riak KV vs. TerminusDB

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service with append-only tables

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Distributed, fault tolerant key-value store

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Time Series DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Graph DBMS

Secondary database models

Document store
RDF store

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	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

cloud.google.com/bigquery

hsqldb.org

www.circonus.com/solutions/time-series-database/

terminusdb.com

Technical documentation

cloud.google.com/bigquery/docs

hsqldb.org/web/hsqlDocsFrame.html

docs.circonus.com/irondb/category/getting-started

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

terminusdb.github.io/terminusdb/#

Developer

Google

Circonus LLC.

OpenSource, formerly Basho Technologies

DataChemist Ltd.

Initial release

2010

2001

2017

2009

2018

Current release

2.7.2, June 2023

V0.10.20, January 2018

3.2.0, December 2022

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

based on BSD license

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPL V3

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

C and C++

Erlang

Prolog, Rust

Server operating systems

hosted

All OS with a Java VM

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

Linux

Linux
OS X

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SQL

Support of SQL

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

SQL-like query language (WOQL)

APIs and other access methods

RESTful HTTP/JSON API

HTTP API

JDBC via HTTP
JDBC
ODBC

HTTP API

HTTP API
Native Erlang Interface

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC
Java

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java, SQL

yes, in Lua

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic, metric affinity per node

Sharding

no "single point of failure"

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

configurable replication factor, datacenter aware

selectable replication factor

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

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 journaling

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

yes, using Riak Security

Role-based access control

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