DBMS > Google Cloud Bigtable vs. IBM Db2 warehouse vs. Snowflake vs. VictoriaMetrics

System Properties Comparison Google Cloud Bigtable vs. IBM Db2 warehouse vs. Snowflake vs. VictoriaMetrics

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Editorial information provided by DB-Engines

Name

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Cloud-based data warehousing service

Cloud-based data warehousing service for structured and semi-structured data

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

Primary database model

Key-value store
Wide column store

Relational DBMS

Time Series DBMS

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

cloud.google.com/bigtable

www.ibm.com/products/db2/warehouse

www.snowflake.com

victoriametrics.com

Technical documentation

cloud.google.com/bigtable/docs

docs.snowflake.net/manuals/index.html

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

Developer

Google

IBM

Snowflake Computing Inc.

VictoriaMetrics

Initial release

2015

2014

2018

Current release

v1.91, May 2023

License

Commercial or Open Source

commercial

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

Server operating systems

hosted

FreeBSD
Linux
macOS
OpenBSD

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

.NET Client API
JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

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

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

PL/SQL, SQL PL

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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