DBMS > Google BigQuery vs. Heroic vs. LevelDB vs. mSQL

System Properties Comparison Google BigQuery vs. Heroic vs. LevelDB vs. mSQL

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Website

cloud.google.com/bigquery

github.com/spotify/heroic

github.com/google/leveldb

hughestech.com.au/products/msql

Technical documentation

cloud.google.com/bigquery/docs

spotify.github.io/heroic

github.com/google/leveldb/blob/main/doc/index.md

Developer

Google

Spotify

Google

Hughes Technologies

Initial release

2010

2014

2011

1994

Current release

1.23, February 2021

4.4, October 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD

commercial

free licenses can be provided

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

Illumos
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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

via Elasticsearch

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

RESTful HTTP/JSON API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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)

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