DBMS > Google BigQuery vs. Google Cloud Spanner vs. Graphite vs. LevelDB vs. SiteWhere

System Properties Comparison Google BigQuery vs. Google Cloud Spanner vs. Graphite vs. LevelDB vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

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

M2M integration platform for persisting/querying time series data

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	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

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

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

cloud.google.com/bigquery

cloud.google.com/spanner

github.com/graphite-project/graphite-web

github.com/google/leveldb

github.com/sitewhere/sitewhere

Technical documentation

cloud.google.com/bigquery/docs

cloud.google.com/spanner/docs

graphite.readthedocs.io

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

sitewhere1.sitewhere.io/index.html

Developer

Google

Chris Davis

Google

SiteWhere

Initial release

2010

2017

2006

2011

2010

Current release

1.23, February 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD

Open Source

Common Public Attribution License Version 1.0

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

Python

C++

Java

Server operating systems

hosted

Linux
Unix

Illumos
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

predefined scheme

Typing

predefined data types such as float or date

yes

Numeric data only

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

Query statements complying to ANSI 2011

APIs and other access methods

RESTful HTTP/JSON API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HTTP API
Sockets

HTTP REST

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Strict serializable isolation

Concurrency

Support for concurrent manipulation of data

yes

locking

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)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Users with fine-grained authorization concept

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