QueryGPT

QueryGPT

Jepsen

Jepsen

Hoply

Hoply

Google Cloud Client Libraries for Python

Google Cloud Client Libraries for Python

Gremlin Guide

Gremlin Guide

Types of RDF Storage

Native

• Main Memory-based
• Disk-based

Non-native

• RDBMS
• Schema-based
• Vertical partitioning
• Hierarchical property table
• Property table
• Schema-free
• Triple table

• NoSQL
• Key-value
• Column Family
• Document store
• Graph database

Blazegraph vs Neptune vs Stardog

DB-Engine Comparison

WikiData Query Service

Wikidata Query

Tigergraph

Tigergraph

Foundations and Trends Series

Foundations and Trends in Information Retrieval
Foundations and Trends in Machine Learning
Foundations and Trends in Web Science
Foundations and Trends in Computer Vision
Foundations and Trends in Databases

Metaphacts

Metaphacts

AWS Neptune

AWS Neptune

AWS vs Azure

Azure	AWS
Storage (Blobs, Tables, Queues, Files)	S3
Virtual Machines	EC2
Autoscale	AutoScaling
Docker Virtual Machine Ext	EC2 Container Service
Blob Storage	Elastic Block Storage
HDInsight	EMR
Cloud Services Websites & Apps	Elastic Beanstalk
Backup	Glacier
Storsimple	Storage Gateway
Import export	Import / export
CDN	Cloudfront
SQL	RDS
DocumentDB	DynamoDB
Managed Cache (Redis)	Elastic Cache
Data Factory	Data Pipeline / Glue
Virtual Network	VPC
ExpressRoute	Direct Connect
Traffic Manager	Route53
Load Balancing	Elastic Load Balancing
Active Directory	IAM
Multi-Factor	Multi-Factor
Operational Insights	CloudTrail
Application Insights	CloudWatch
Event Hubs	Kinesis
Notification Hubs	SNS
Key Vault	Key Management Service
Resource Manager	Cloud Formation
API Management	API Gateway
Automation	Opsworks
Batch	SQS
Search	CloudSearch
Service Bus	SWF
Stream Analytics	Kinesis
Biztalk	SES
Machine Learning (preview)	Machine Learning
Functions	Lambda
Gets more expensive as you use more on the 'you only pay for what you use model' (especially Linux instances)	Less expensive as you use more on the 'you only pay for what you use model'   (has plenty of linux options and windows options are priced the same as azure)
Generally, slower in services	Generally, faster in services
Very confusing naming for services some of which are not even services but just reused applications in the cloud	Service names are distinguishable and clear
Azure charges by the minute	AWS charges by the hour
ML and data analytics options are not that great.  Azure only has cosmodb, hdinsight, event hub, storage, its AI services are not great either, tight coupling to azure windows services, not ideal for data science work - with azure for non-windows type work is not seamless. CosmoDB is a strong option –it supports documentdb, mongodb, property graph, cassandra, table – not perfect but ok.	Data Pipeline  Kinesis  S3  Deep Learning library support + AMIs,  Support for GPU instances  More flexible DBs, But no multi-model option, Redshift, EMR (supports spark, flink, presto, hbase, hive, pig), glue, athena, elasticsearch, cloudsearch, clustering is easier for linux machines (can you see running hadoop on windows?), AWS has neptune that supports property graphs, rdf, sparql,  tinkerpop.

azure vs aws service mappings