DBMS > Google BigQuery vs. Google Cloud Spanner vs. Sadas Engine vs. VictoriaMetrics

System Properties Comparison Google BigQuery vs. Google Cloud Spanner vs. Sadas Engine vs. VictoriaMetrics

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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.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Relational DBMS

Time Series DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

cloud.google.com/bigquery

cloud.google.com/spanner

www.sadasengine.com

victoriametrics.com

Technical documentation

cloud.google.com/bigquery/docs

cloud.google.com/spanner/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Google

SADAS s.r.l.

VictoriaMetrics

Initial release

2010

2017

2006

2018

Current release

8.0

v1.91, May 2023

License

Commercial or Open Source

commercial

free trial version available

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

C++

Server operating systems

hosted

AIX
Linux
Windows

FreeBSD
Linux
macOS
OpenBSD

Data scheme

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

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

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

JDBC
ODBC
Proprietary protocol

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

none

Synchronous replication

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

Eventual Consistency

Foreign keys

Referential integrity

yes

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

yes

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

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

managed by 'Learn by Usage'

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)

Access rights for users, groups and roles according to SQL-standard

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