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Google Cloud Study
Jam
Session 4
Session Agenda
1. Cloud Storage
2. Database Services
Database Services
Types of Databases
Proprietary + Confidential
Your database choice depends on your needs
Availability
Consistency Cost Future proofing Data model
Multi-Region Skill Set Operations Compatibility
Open standard
Proprietary + Confidential
In-Memory Database in the Cloud
Proprietary + Confidential
Memorystore
Fully Managed Redis and Memcached database for sub-millisecond data
access
Proprietary + Confidential
Real-time analytics
For workloads that require microseconds latency,
Memorystore is a scalable, secure, highly available
in-memory service
Fully compatible with Redis and
Memcached, offering easy migration
for Redis and Memcached workloads.
Over 90% of the top 100 Google
Cloud customers use Memorystore.
Example use
cases
Caching
Session store
Leaderboard
Jobs and queues
Fast data ingestion
Proprietary + Confidential
Relational Databases in the Cloud
Proprietary + Confidential
Cloud SQL
Managed Database Platform for MySQL, PostgreSQL and SQL Server Databases
Fully Managed & Enterprise Ready
Easy to set up, operate, and scale
Trusted
Enterprise-grade data protection, security and governance
Developer Friendly
Application centric observability and API-first administration
Supports PostgreSQL, MySQL and SQL
Server
Full compatibility with source database engines
More than
90%
of Google Cloud’s top 100 customers use Cloud
SQL
Cloud SQL
Fully managed relational database
service
Proprietary + Confidential
Spanner
Enterprise-grade, globally-distributed, and strongly-consistent managed
SQL database service built for the cloud
What is
Spanner?
Relational
ACID transactions,
SQL, Schemas
Horizontally
scalable
Distributed RDBMS,
Near unlimited scale
Fully managed
++
Simplified administration,
Enterprise grade
99.999% uptime SLA
Automatic sharding
Superior price-performance
No maintenance downtime
Zero-touch global replication
Automatic failure recovery
RPO =0, RTO = 0
Online, unlimited scaling
Security and compliance
Strong external consistency
Spanner processes over 2 billion requests per second at
peak Spanner has more than 6 exabytes of data under
management
Proprietary + Confidential
Non-Relational Databases in the
Cloud
Proprietary + Confidential
Firestore
Serverless NoSQL document database built for automatic scaling, high performance in the cloud
Firestore
Unlock application innovation with simplicity, speed and confidence
Firestore by the numbers
Over
4 million
databases have been created in Firestore
Firestore apps power more than
1 billion
monthly active end-users using Firebase Auth
Serverless, document database
JSON-compatible data model, serializable ACID
transactions, elastic scalability, up to 99.999% availability
SLA, pay only for what you consume
Secure, backend as a service
Connect directly and securely to the database, making
middle tiers optional
Real-time sync & offline access
Built-in data syncing, and fallback to on-device caching
when a client loses network connectivity
Well integrated
Deliver results faster with native integrations with Google
Cloud, Firebase and 3rd party developer services via
Extensions
Proprietary + Confidential
Bigtable
Globally distributed, fully managed NoSQL database with high performance
at any scale
Bigtable
Real-time data serving and operational analytics at any scale
Bigtable has over 10
Exabytes of data under
management
Bigtable processes more than 5
Billion requests per second at peak
High throughput
Millions of RPS, Predictable
single-digit ms latency
Compatible
HBase API, Apache Spark,
Integrates with Apache Beam
ecosystem
Flexibility at scale
Flexible schema, eventual consistency*
Example use
cases
Fraud detection
Data Fabric/Operational
Data Store
Time Series
Product/Content metadata
* Strong consistency within a single cluster
Personalization
Customer 360
Battle tested by
Google
Proprietary + Confidential
68%
of companies are unable to realize measurable value from data.
More duplication
More silos
More complexity
More point
solutions More
security risk
Data is big and
multi-format.
Data requires more than
SQL.
Data reaches
everyone.
High costs
Constant Capacity
Planning Low
productivity
Limited access
Data
unavailable
Poor SLAs
Unclear compliance
Accenture, Closing the Data Value Gap
BigQuery
The core of
Google’s Data
Cloud to power
your data-driven
innovation.
BigQuery
Limitless
data
Limitless
reach
Limitless
workloads
Limitless
Data
Why BigQuery?
Limitless
data
Identity management
Distributed
Memory
Shuffle Tier
BigQuery
Completely elastic
Distributed storage and compute with ultra-high
bandwidth including distribute petabyte scale in-memory
storage for temp data and state:
● Auto-start and auto-pause
● 0-Second warm up to get maximum performance
● Accelerate queries in flight
● No performance cliff due to local capacity saturation
● Immune to large-scale hardware failures
Google Cloud
Security
Petabit network
Hardware infrastructure
Collect Process Activate
Store Analyze Empowe
r
Replicated,
Distributed
Storage
(99.9999999999%
)
High-Available
Cluster
Compute
(Dremel)
VS
● Simplifies capacity management
● Dynamically adjusts to demand
● Plan, manage, pay VMs
● Limit use data due to capacity
restrictions
Completely
serverless
Why BigQuery?
Limitless
data
All your data types in one
platform
● Structured
● Semi-structured (JSON)
● Unstructured (text, images, docs)
● Parquet
● JSON
● Nested Tables
● Geospatial
VS
● Manage pipelines and
integrations
● Miss value from
unsupported data types
● Simplifies data type
management with a
unified ecosystem
● Provides unique data
capabilities (geospatial)
All data
types
Limitless
Workloads
Why BigQuery?
All
workloads
Machine Learning for all Built-in
ML with SQL
● Execute, iterate, and automate ML
initiatives all within BigQuery using
predefined models
● Leverage external models developed in
Tensorflow directly from SQL
● Export developed models for use in
Vertex AI
VS
● Provide ML access to
more users through a
simple SQL interface
● Require every ML use
case to go through more
specialized systems that
require advanced skill
sets
Built-in AI/ML |
BQML
Limitless
Reach
Open
Everyone can analyze billions of
rows of data in Sheets, without
specialized DW knowledge
No additional charge with any
Google Workspace plan - Enterprise,
Business, and Personal (free)
Connected Sheets for
Looker
Sheet
s
Easy to use and
share
Intelligent
Familiar interface
Simple and flexible
analysis
+
BigQuery
Analyze petabytes
of data
Complex queries
Reduce time to insights
Looker
60+ database
connections available
Modeled data
Integrated insights
Connected
Sheets
Analyze billions of rows
of data in Sheets,
without any need for
specialized knowledge
For
everyone
BI Beyond
Dashboards
Spreadsheet Analysis of Tomorrow. Today.
Thank You

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GDSC Google Cloud Study jam Web Bootcamp - Day-4 Session 4

  • 2. Session Agenda 1. Cloud Storage 2. Database Services
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 11.
  • 13. Proprietary + Confidential Your database choice depends on your needs Availability Consistency Cost Future proofing Data model Multi-Region Skill Set Operations Compatibility Open standard
  • 14. Proprietary + Confidential In-Memory Database in the Cloud
  • 15. Proprietary + Confidential Memorystore Fully Managed Redis and Memcached database for sub-millisecond data access
  • 16. Proprietary + Confidential Real-time analytics For workloads that require microseconds latency, Memorystore is a scalable, secure, highly available in-memory service Fully compatible with Redis and Memcached, offering easy migration for Redis and Memcached workloads. Over 90% of the top 100 Google Cloud customers use Memorystore. Example use cases Caching Session store Leaderboard Jobs and queues Fast data ingestion
  • 17. Proprietary + Confidential Relational Databases in the Cloud
  • 18. Proprietary + Confidential Cloud SQL Managed Database Platform for MySQL, PostgreSQL and SQL Server Databases
  • 19. Fully Managed & Enterprise Ready Easy to set up, operate, and scale Trusted Enterprise-grade data protection, security and governance Developer Friendly Application centric observability and API-first administration Supports PostgreSQL, MySQL and SQL Server Full compatibility with source database engines More than 90% of Google Cloud’s top 100 customers use Cloud SQL Cloud SQL Fully managed relational database service
  • 20. Proprietary + Confidential Spanner Enterprise-grade, globally-distributed, and strongly-consistent managed SQL database service built for the cloud
  • 21. What is Spanner? Relational ACID transactions, SQL, Schemas Horizontally scalable Distributed RDBMS, Near unlimited scale Fully managed ++ Simplified administration, Enterprise grade 99.999% uptime SLA Automatic sharding Superior price-performance No maintenance downtime Zero-touch global replication Automatic failure recovery RPO =0, RTO = 0 Online, unlimited scaling Security and compliance Strong external consistency Spanner processes over 2 billion requests per second at peak Spanner has more than 6 exabytes of data under management
  • 23. Proprietary + Confidential Firestore Serverless NoSQL document database built for automatic scaling, high performance in the cloud
  • 24. Firestore Unlock application innovation with simplicity, speed and confidence Firestore by the numbers Over 4 million databases have been created in Firestore Firestore apps power more than 1 billion monthly active end-users using Firebase Auth Serverless, document database JSON-compatible data model, serializable ACID transactions, elastic scalability, up to 99.999% availability SLA, pay only for what you consume Secure, backend as a service Connect directly and securely to the database, making middle tiers optional Real-time sync & offline access Built-in data syncing, and fallback to on-device caching when a client loses network connectivity Well integrated Deliver results faster with native integrations with Google Cloud, Firebase and 3rd party developer services via Extensions
  • 25. Proprietary + Confidential Bigtable Globally distributed, fully managed NoSQL database with high performance at any scale
  • 26. Bigtable Real-time data serving and operational analytics at any scale Bigtable has over 10 Exabytes of data under management Bigtable processes more than 5 Billion requests per second at peak High throughput Millions of RPS, Predictable single-digit ms latency Compatible HBase API, Apache Spark, Integrates with Apache Beam ecosystem Flexibility at scale Flexible schema, eventual consistency* Example use cases Fraud detection Data Fabric/Operational Data Store Time Series Product/Content metadata * Strong consistency within a single cluster Personalization Customer 360 Battle tested by Google
  • 27. Proprietary + Confidential 68% of companies are unable to realize measurable value from data. More duplication More silos More complexity More point solutions More security risk Data is big and multi-format. Data requires more than SQL. Data reaches everyone. High costs Constant Capacity Planning Low productivity Limited access Data unavailable Poor SLAs Unclear compliance Accenture, Closing the Data Value Gap
  • 28. BigQuery The core of Google’s Data Cloud to power your data-driven innovation. BigQuery Limitless data Limitless reach Limitless workloads
  • 30. Why BigQuery? Limitless data Identity management Distributed Memory Shuffle Tier BigQuery Completely elastic Distributed storage and compute with ultra-high bandwidth including distribute petabyte scale in-memory storage for temp data and state: ● Auto-start and auto-pause ● 0-Second warm up to get maximum performance ● Accelerate queries in flight ● No performance cliff due to local capacity saturation ● Immune to large-scale hardware failures Google Cloud Security Petabit network Hardware infrastructure Collect Process Activate Store Analyze Empowe r Replicated, Distributed Storage (99.9999999999% ) High-Available Cluster Compute (Dremel) VS ● Simplifies capacity management ● Dynamically adjusts to demand ● Plan, manage, pay VMs ● Limit use data due to capacity restrictions Completely serverless
  • 31. Why BigQuery? Limitless data All your data types in one platform ● Structured ● Semi-structured (JSON) ● Unstructured (text, images, docs) ● Parquet ● JSON ● Nested Tables ● Geospatial VS ● Manage pipelines and integrations ● Miss value from unsupported data types ● Simplifies data type management with a unified ecosystem ● Provides unique data capabilities (geospatial) All data types
  • 33. Why BigQuery? All workloads Machine Learning for all Built-in ML with SQL ● Execute, iterate, and automate ML initiatives all within BigQuery using predefined models ● Leverage external models developed in Tensorflow directly from SQL ● Export developed models for use in Vertex AI VS ● Provide ML access to more users through a simple SQL interface ● Require every ML use case to go through more specialized systems that require advanced skill sets Built-in AI/ML | BQML
  • 35. Open Everyone can analyze billions of rows of data in Sheets, without specialized DW knowledge No additional charge with any Google Workspace plan - Enterprise, Business, and Personal (free) Connected Sheets for Looker Sheet s Easy to use and share Intelligent Familiar interface Simple and flexible analysis + BigQuery Analyze petabytes of data Complex queries Reduce time to insights Looker 60+ database connections available Modeled data Integrated insights Connected Sheets Analyze billions of rows of data in Sheets, without any need for specialized knowledge For everyone BI Beyond Dashboards Spreadsheet Analysis of Tomorrow. Today.