SlideShare a Scribd company logo

Thrift vs Protocol Buffers vs Avro - Biased Comparison

Igor Anishchenko Odessa Java TechTalks Lohika - May, 2012 Let's take a step back and compare data serialization formats, of which there are plenty. What are the key differences between Apache Thrift, Google Protocol Buffers and Apache Avro. Which is "The Best"? Truth of the matter is, they are all very good and each has its own strong points. Hence, the answer is as much of a personal choice, as well as understanding of the historical context for each, and correctly identifying your own, individual requirements.

1 of 51
Download to read offline
PB vs. Thrift vs. Avro



    Author: Igor Anishchenko

                     Lohika - May, 2012
Problem Statement
      Simple Distributed Architecture

                serialize      deserialize



                deserialize      serialize




  •    Basic questions are:

       •   What kind of protocol to use, and what data to transmit?

       •   Efficient mechanism for storing and exchanging data

       •   What to do with requests on the server side?
…and you want to scale your servers...


 •   When you grow beyond a simple architecture, you want..
     •   flexibility
     •   ability to grow
     •   latency
     •   and of course - you want it to be simple
How components talk

 •   Database protocols - fine.
 •   HTTP + maybe JSON/XML on the front - cool.
How components talk

 •   Database protocols - fine.
 •   HTTP + maybe JSON/XML on the front - cool.

 • But most of the times you have
     internal APIs.
Hasn't this been done before? (yes)


  •   SOAP
  •   CORBA
  •   DCOM, COM+
  •   JSON, Plain Text, XML

Recommended

Scalability, Availability & Stability Patterns
Scalability, Availability & Stability PatternsScalability, Availability & Stability Patterns
Scalability, Availability & Stability PatternsJonas Bonér
 
Introduction to Redis
Introduction to RedisIntroduction to Redis
Introduction to RedisDvir Volk
 
Espresso: LinkedIn's Distributed Data Serving Platform (Paper)
Espresso: LinkedIn's Distributed Data Serving Platform (Paper)Espresso: LinkedIn's Distributed Data Serving Platform (Paper)
Espresso: LinkedIn's Distributed Data Serving Platform (Paper)Amy W. Tang
 
Introduction to Apache ZooKeeper
Introduction to Apache ZooKeeperIntroduction to Apache ZooKeeper
Introduction to Apache ZooKeeperSaurav Haloi
 
Introduction to MongoDB
Introduction to MongoDBIntroduction to MongoDB
Introduction to MongoDBMike Dirolf
 
Apache Kafka Architecture & Fundamentals Explained
Apache Kafka Architecture & Fundamentals ExplainedApache Kafka Architecture & Fundamentals Explained
Apache Kafka Architecture & Fundamentals Explainedconfluent
 
Capabilities for Resources and Effects
Capabilities for Resources and EffectsCapabilities for Resources and Effects
Capabilities for Resources and EffectsMartin Odersky
 
Redis data modeling examples
Redis data modeling examplesRedis data modeling examples
Redis data modeling examplesTerry Cho
 

More Related Content

What's hot

Working with JSON Data in PostgreSQL vs. MongoDB
Working with JSON Data in PostgreSQL vs. MongoDBWorking with JSON Data in PostgreSQL vs. MongoDB
Working with JSON Data in PostgreSQL vs. MongoDBScaleGrid.io
 
Introduction to memcached
Introduction to memcachedIntroduction to memcached
Introduction to memcachedJurriaan Persyn
 
Schema-on-Read vs Schema-on-Write
Schema-on-Read vs Schema-on-WriteSchema-on-Read vs Schema-on-Write
Schema-on-Read vs Schema-on-WriteAmr Awadallah
 
Presto: Fast SQL-on-Anything (including Delta Lake, Snowflake, Elasticsearch ...
Presto: Fast SQL-on-Anything (including Delta Lake, Snowflake, Elasticsearch ...Presto: Fast SQL-on-Anything (including Delta Lake, Snowflake, Elasticsearch ...
Presto: Fast SQL-on-Anything (including Delta Lake, Snowflake, Elasticsearch ...Databricks
 
Polyglot persistence @ netflix (CDE Meetup)
Polyglot persistence @ netflix (CDE Meetup) Polyglot persistence @ netflix (CDE Meetup)
Polyglot persistence @ netflix (CDE Meetup) Roopa Tangirala
 
Stability Patterns for Microservices
Stability Patterns for MicroservicesStability Patterns for Microservices
Stability Patterns for Microservicespflueras
 
Parquet - Data I/O - Philadelphia 2013
Parquet - Data I/O - Philadelphia 2013Parquet - Data I/O - Philadelphia 2013
Parquet - Data I/O - Philadelphia 2013larsgeorge
 
MongoDB Fundamentals
MongoDB FundamentalsMongoDB Fundamentals
MongoDB FundamentalsMongoDB
 
On-boarding with JanusGraph Performance
On-boarding with JanusGraph PerformanceOn-boarding with JanusGraph Performance
On-boarding with JanusGraph PerformanceChin Huang
 
A topology of memory leaks on the JVM
A topology of memory leaks on the JVMA topology of memory leaks on the JVM
A topology of memory leaks on the JVMRafael Winterhalter
 
RocksDB detail
RocksDB detailRocksDB detail
RocksDB detailMIJIN AN
 
Kafka and Avro with Confluent Schema Registry
Kafka and Avro with Confluent Schema RegistryKafka and Avro with Confluent Schema Registry
Kafka and Avro with Confluent Schema RegistryJean-Paul Azar
 
Hive Bucketing in Apache Spark with Tejas Patil
Hive Bucketing in Apache Spark with Tejas PatilHive Bucketing in Apache Spark with Tejas Patil
Hive Bucketing in Apache Spark with Tejas PatilDatabricks
 
Salvatore Sanfilippo – How Redis Cluster works, and why - NoSQL matters Barce...
Salvatore Sanfilippo – How Redis Cluster works, and why - NoSQL matters Barce...Salvatore Sanfilippo – How Redis Cluster works, and why - NoSQL matters Barce...
Salvatore Sanfilippo – How Redis Cluster works, and why - NoSQL matters Barce...NoSQLmatters
 
Efficient Data Storage for Analytics with Parquet 2.0 - Hadoop Summit 2014
Efficient Data Storage for Analytics with Parquet 2.0 - Hadoop Summit 2014Efficient Data Storage for Analytics with Parquet 2.0 - Hadoop Summit 2014
Efficient Data Storage for Analytics with Parquet 2.0 - Hadoop Summit 2014Julien Le Dem
 
Introduction to Node.js
Introduction to Node.jsIntroduction to Node.js
Introduction to Node.jsVikash Singh
 
Monitoring Hadoop with Prometheus (Hadoop User Group Ireland, December 2015)
Monitoring Hadoop with Prometheus (Hadoop User Group Ireland, December 2015)Monitoring Hadoop with Prometheus (Hadoop User Group Ireland, December 2015)
Monitoring Hadoop with Prometheus (Hadoop User Group Ireland, December 2015)Brian Brazil
 
Introduction to Redis
Introduction to RedisIntroduction to Redis
Introduction to RedisArnab Mitra
 
Dynamic Priorities for Apache Spark Application’s Resource Allocations with M...
Dynamic Priorities for Apache Spark Application’s Resource Allocations with M...Dynamic Priorities for Apache Spark Application’s Resource Allocations with M...
Dynamic Priorities for Apache Spark Application’s Resource Allocations with M...Databricks
 
Presto: Optimizing Performance of SQL-on-Anything Engine
Presto: Optimizing Performance of SQL-on-Anything EnginePresto: Optimizing Performance of SQL-on-Anything Engine
Presto: Optimizing Performance of SQL-on-Anything EngineDataWorks Summit
 

What's hot (20)

Working with JSON Data in PostgreSQL vs. MongoDB
Working with JSON Data in PostgreSQL vs. MongoDBWorking with JSON Data in PostgreSQL vs. MongoDB
Working with JSON Data in PostgreSQL vs. MongoDB
 
Introduction to memcached
Introduction to memcachedIntroduction to memcached
Introduction to memcached
 
Schema-on-Read vs Schema-on-Write
Schema-on-Read vs Schema-on-WriteSchema-on-Read vs Schema-on-Write
Schema-on-Read vs Schema-on-Write
 
Presto: Fast SQL-on-Anything (including Delta Lake, Snowflake, Elasticsearch ...
Presto: Fast SQL-on-Anything (including Delta Lake, Snowflake, Elasticsearch ...Presto: Fast SQL-on-Anything (including Delta Lake, Snowflake, Elasticsearch ...
Presto: Fast SQL-on-Anything (including Delta Lake, Snowflake, Elasticsearch ...
 
Polyglot persistence @ netflix (CDE Meetup)
Polyglot persistence @ netflix (CDE Meetup) Polyglot persistence @ netflix (CDE Meetup)
Polyglot persistence @ netflix (CDE Meetup)
 
Stability Patterns for Microservices
Stability Patterns for MicroservicesStability Patterns for Microservices
Stability Patterns for Microservices
 
Parquet - Data I/O - Philadelphia 2013
Parquet - Data I/O - Philadelphia 2013Parquet - Data I/O - Philadelphia 2013
Parquet - Data I/O - Philadelphia 2013
 
MongoDB Fundamentals
MongoDB FundamentalsMongoDB Fundamentals
MongoDB Fundamentals
 
On-boarding with JanusGraph Performance
On-boarding with JanusGraph PerformanceOn-boarding with JanusGraph Performance
On-boarding with JanusGraph Performance
 
A topology of memory leaks on the JVM
A topology of memory leaks on the JVMA topology of memory leaks on the JVM
A topology of memory leaks on the JVM
 
RocksDB detail
RocksDB detailRocksDB detail
RocksDB detail
 
Kafka and Avro with Confluent Schema Registry
Kafka and Avro with Confluent Schema RegistryKafka and Avro with Confluent Schema Registry
Kafka and Avro with Confluent Schema Registry
 
Hive Bucketing in Apache Spark with Tejas Patil
Hive Bucketing in Apache Spark with Tejas PatilHive Bucketing in Apache Spark with Tejas Patil
Hive Bucketing in Apache Spark with Tejas Patil
 
Salvatore Sanfilippo – How Redis Cluster works, and why - NoSQL matters Barce...
Salvatore Sanfilippo – How Redis Cluster works, and why - NoSQL matters Barce...Salvatore Sanfilippo – How Redis Cluster works, and why - NoSQL matters Barce...
Salvatore Sanfilippo – How Redis Cluster works, and why - NoSQL matters Barce...
 
Efficient Data Storage for Analytics with Parquet 2.0 - Hadoop Summit 2014
Efficient Data Storage for Analytics with Parquet 2.0 - Hadoop Summit 2014Efficient Data Storage for Analytics with Parquet 2.0 - Hadoop Summit 2014
Efficient Data Storage for Analytics with Parquet 2.0 - Hadoop Summit 2014
 
Introduction to Node.js
Introduction to Node.jsIntroduction to Node.js
Introduction to Node.js
 
Monitoring Hadoop with Prometheus (Hadoop User Group Ireland, December 2015)
Monitoring Hadoop with Prometheus (Hadoop User Group Ireland, December 2015)Monitoring Hadoop with Prometheus (Hadoop User Group Ireland, December 2015)
Monitoring Hadoop with Prometheus (Hadoop User Group Ireland, December 2015)
 
Introduction to Redis
Introduction to RedisIntroduction to Redis
Introduction to Redis
 
Dynamic Priorities for Apache Spark Application’s Resource Allocations with M...
Dynamic Priorities for Apache Spark Application’s Resource Allocations with M...Dynamic Priorities for Apache Spark Application’s Resource Allocations with M...
Dynamic Priorities for Apache Spark Application’s Resource Allocations with M...
 
Presto: Optimizing Performance of SQL-on-Anything Engine
Presto: Optimizing Performance of SQL-on-Anything EnginePresto: Optimizing Performance of SQL-on-Anything Engine
Presto: Optimizing Performance of SQL-on-Anything Engine
 

Similar to Thrift vs Protocol Buffers vs Avro - Biased Comparison

C # (C Sharp).pptx
C # (C Sharp).pptxC # (C Sharp).pptx
C # (C Sharp).pptxSnapeSever
 
Understanding Character Encodings
Understanding Character EncodingsUnderstanding Character Encodings
Understanding Character EncodingsMobisoft Infotech
 
Enforcing API Design Rules for High Quality Code Generation
Enforcing API Design Rules for High Quality Code GenerationEnforcing API Design Rules for High Quality Code Generation
Enforcing API Design Rules for High Quality Code GenerationTim Burks
 
Apache Avro in LivePerson [Hebrew]
Apache Avro in LivePerson [Hebrew]Apache Avro in LivePerson [Hebrew]
Apache Avro in LivePerson [Hebrew]LivePerson
 
Programming Languages #devcon2013
Programming Languages #devcon2013Programming Languages #devcon2013
Programming Languages #devcon2013Iván Montes
 
python presntation 2.pptx
python presntation 2.pptxpython presntation 2.pptx
python presntation 2.pptxArpittripathi45
 
"Source Code Abstracts Classification Using CNN", Vadim Markovtsev, Lead Soft...
"Source Code Abstracts Classification Using CNN", Vadim Markovtsev, Lead Soft..."Source Code Abstracts Classification Using CNN", Vadim Markovtsev, Lead Soft...
"Source Code Abstracts Classification Using CNN", Vadim Markovtsev, Lead Soft...Dataconomy Media
 
CHAPTER 5 mechanical engineeringasaaa.pptx
CHAPTER 5 mechanical engineeringasaaa.pptxCHAPTER 5 mechanical engineeringasaaa.pptx
CHAPTER 5 mechanical engineeringasaaa.pptxSadhilAggarwal
 
Building scalable and language independent java services using apache thrift
Building scalable and language independent java services using apache thriftBuilding scalable and language independent java services using apache thrift
Building scalable and language independent java services using apache thriftTalentica Software
 
Programming with Python: Week 1
Programming with Python: Week 1Programming with Python: Week 1
Programming with Python: Week 1Ahmet Bulut
 
Building scalable and language-independent Java services using Apache Thrift ...
Building scalable and language-independent Java services using Apache Thrift ...Building scalable and language-independent Java services using Apache Thrift ...
Building scalable and language-independent Java services using Apache Thrift ...IndicThreads
 
Apache Arrow Workshop at VLDB 2019 / BOSS Session
Apache Arrow Workshop at VLDB 2019 / BOSS SessionApache Arrow Workshop at VLDB 2019 / BOSS Session
Apache Arrow Workshop at VLDB 2019 / BOSS SessionWes McKinney
 
Lag Sucks! GDC 2012
Lag Sucks! GDC 2012Lag Sucks! GDC 2012
Lag Sucks! GDC 2012realjenius
 
8. Software Development Security
8. Software Development Security8. Software Development Security
8. Software Development SecuritySam Bowne
 
How to Write the Fastest JSON Parser/Writer in the World
How to Write the Fastest JSON Parser/Writer in the WorldHow to Write the Fastest JSON Parser/Writer in the World
How to Write the Fastest JSON Parser/Writer in the WorldMilo Yip
 
Introduction to Python Programming
Introduction to Python ProgrammingIntroduction to Python Programming
Introduction to Python ProgrammingAkhil Kaushik
 

Similar to Thrift vs Protocol Buffers vs Avro - Biased Comparison (20)

C # (C Sharp).pptx
C # (C Sharp).pptxC # (C Sharp).pptx
C # (C Sharp).pptx
 
Understanding Character Encodings
Understanding Character EncodingsUnderstanding Character Encodings
Understanding Character Encodings
 
Enforcing API Design Rules for High Quality Code Generation
Enforcing API Design Rules for High Quality Code GenerationEnforcing API Design Rules for High Quality Code Generation
Enforcing API Design Rules for High Quality Code Generation
 
Apache Avro in LivePerson [Hebrew]
Apache Avro in LivePerson [Hebrew]Apache Avro in LivePerson [Hebrew]
Apache Avro in LivePerson [Hebrew]
 
Programming Languages #devcon2013
Programming Languages #devcon2013Programming Languages #devcon2013
Programming Languages #devcon2013
 
python presntation 2.pptx
python presntation 2.pptxpython presntation 2.pptx
python presntation 2.pptx
 
"Source Code Abstracts Classification Using CNN", Vadim Markovtsev, Lead Soft...
"Source Code Abstracts Classification Using CNN", Vadim Markovtsev, Lead Soft..."Source Code Abstracts Classification Using CNN", Vadim Markovtsev, Lead Soft...
"Source Code Abstracts Classification Using CNN", Vadim Markovtsev, Lead Soft...
 
Building custom kernels for IPython
Building custom kernels for IPythonBuilding custom kernels for IPython
Building custom kernels for IPython
 
CHAPTER 5 mechanical engineeringasaaa.pptx
CHAPTER 5 mechanical engineeringasaaa.pptxCHAPTER 5 mechanical engineeringasaaa.pptx
CHAPTER 5 mechanical engineeringasaaa.pptx
 
Building scalable and language independent java services using apache thrift
Building scalable and language independent java services using apache thriftBuilding scalable and language independent java services using apache thrift
Building scalable and language independent java services using apache thrift
 
I18n
I18nI18n
I18n
 
Programming with Python: Week 1
Programming with Python: Week 1Programming with Python: Week 1
Programming with Python: Week 1
 
Building scalable and language-independent Java services using Apache Thrift ...
Building scalable and language-independent Java services using Apache Thrift ...Building scalable and language-independent Java services using Apache Thrift ...
Building scalable and language-independent Java services using Apache Thrift ...
 
Apache Arrow Workshop at VLDB 2019 / BOSS Session
Apache Arrow Workshop at VLDB 2019 / BOSS SessionApache Arrow Workshop at VLDB 2019 / BOSS Session
Apache Arrow Workshop at VLDB 2019 / BOSS Session
 
Lecture 2
Lecture 2Lecture 2
Lecture 2
 
Lag Sucks! GDC 2012
Lag Sucks! GDC 2012Lag Sucks! GDC 2012
Lag Sucks! GDC 2012
 
Python programming 2nd
Python programming 2ndPython programming 2nd
Python programming 2nd
 
8. Software Development Security
8. Software Development Security8. Software Development Security
8. Software Development Security
 
How to Write the Fastest JSON Parser/Writer in the World
How to Write the Fastest JSON Parser/Writer in the WorldHow to Write the Fastest JSON Parser/Writer in the World
How to Write the Fastest JSON Parser/Writer in the World
 
Introduction to Python Programming
Introduction to Python ProgrammingIntroduction to Python Programming
Introduction to Python Programming
 

Recently uploaded

Unleash the Solace Pub Sub connector | Banaglore MuleSoft Meetup #31
Unleash the Solace Pub Sub connector | Banaglore MuleSoft Meetup #31Unleash the Solace Pub Sub connector | Banaglore MuleSoft Meetup #31
Unleash the Solace Pub Sub connector | Banaglore MuleSoft Meetup #31shyamraj55
 
"Platform Engineering with Development Containers", Igor Fesenko
"Platform Engineering with Development Containers", Igor Fesenko"Platform Engineering with Development Containers", Igor Fesenko
"Platform Engineering with Development Containers", Igor FesenkoFwdays
 
Roundtable_-_API_Research__Testing_Tools.pdf
Roundtable_-_API_Research__Testing_Tools.pdfRoundtable_-_API_Research__Testing_Tools.pdf
Roundtable_-_API_Research__Testing_Tools.pdfMostafa Higazy
 
"Testing of Helm Charts or There and Back Again", Yura Rochniak
"Testing of Helm Charts or There and Back Again", Yura Rochniak"Testing of Helm Charts or There and Back Again", Yura Rochniak
"Testing of Helm Charts or There and Back Again", Yura RochniakFwdays
 
LF Energy Webinar: Introduction to TROLIE
LF Energy Webinar: Introduction to TROLIELF Energy Webinar: Introduction to TROLIE
LF Energy Webinar: Introduction to TROLIEDanBrown980551
 
"How we created an SRE team in Temabit as a part of FOZZY Group in conditions...
"How we created an SRE team in Temabit as a part of FOZZY Group in conditions..."How we created an SRE team in Temabit as a part of FOZZY Group in conditions...
"How we created an SRE team in Temabit as a part of FOZZY Group in conditions...Fwdays
 
"AIRe - AI Reliability Engineering", Denys Vasyliev
"AIRe - AI Reliability Engineering", Denys Vasyliev"AIRe - AI Reliability Engineering", Denys Vasyliev
"AIRe - AI Reliability Engineering", Denys VasylievFwdays
 
Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...
Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...
Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...Product School
 
Are Human-generated Demonstrations Necessary for In-context Learning?
Are Human-generated Demonstrations Necessary for In-context Learning?Are Human-generated Demonstrations Necessary for In-context Learning?
Are Human-generated Demonstrations Necessary for In-context Learning?MENGSAYLOEM1
 
How AI and ChatGPT are changing cybersecurity forever.pptx
How AI and ChatGPT are changing cybersecurity forever.pptxHow AI and ChatGPT are changing cybersecurity forever.pptx
How AI and ChatGPT are changing cybersecurity forever.pptxInfosec
 
How we think about an advisor tech stack
How we think about an advisor tech stackHow we think about an advisor tech stack
How we think about an advisor tech stackSummit
 
ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...
ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...
ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...Neo4j
 
"DevOps Practisting Platform on EKS with Karpenter autoscaling", Dmytro Kozhevin
"DevOps Practisting Platform on EKS with Karpenter autoscaling", Dmytro Kozhevin"DevOps Practisting Platform on EKS with Karpenter autoscaling", Dmytro Kozhevin
"DevOps Practisting Platform on EKS with Karpenter autoscaling", Dmytro KozhevinFwdays
 
How to write an effective Cyber Incident Response Plan
How to write an effective Cyber Incident Response PlanHow to write an effective Cyber Incident Response Plan
How to write an effective Cyber Incident Response PlanDatabarracks
 
Enterprise Architecture As Strategy - Book Review
Enterprise Architecture As Strategy - Book ReviewEnterprise Architecture As Strategy - Book Review
Enterprise Architecture As Strategy - Book ReviewAshraf Fouad
 
Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...
Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...
Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...DianaGray10
 
Centralized TLS Certificates Management Using Vault PKI + Cert-Manager
Centralized TLS Certificates Management Using Vault PKI + Cert-ManagerCentralized TLS Certificates Management Using Vault PKI + Cert-Manager
Centralized TLS Certificates Management Using Vault PKI + Cert-ManagerSaiLinnThu2
 
The Future of Product, by Founder & CEO, Product School
The Future of Product, by Founder & CEO, Product SchoolThe Future of Product, by Founder & CEO, Product School
The Future of Product, by Founder & CEO, Product SchoolProduct School
 
The Art of the Possible with Graph by Dr Jim Webber Neo4j.pptx
The Art of the Possible with Graph by Dr Jim Webber Neo4j.pptxThe Art of the Possible with Graph by Dr Jim Webber Neo4j.pptx
The Art of the Possible with Graph by Dr Jim Webber Neo4j.pptxNeo4j
 
Relationship Counselling: From Disjointed Features to Product-First Thinking ...
Relationship Counselling: From Disjointed Features to Product-First Thinking ...Relationship Counselling: From Disjointed Features to Product-First Thinking ...
Relationship Counselling: From Disjointed Features to Product-First Thinking ...Product School
 

Recently uploaded (20)

Unleash the Solace Pub Sub connector | Banaglore MuleSoft Meetup #31
Unleash the Solace Pub Sub connector | Banaglore MuleSoft Meetup #31Unleash the Solace Pub Sub connector | Banaglore MuleSoft Meetup #31
Unleash the Solace Pub Sub connector | Banaglore MuleSoft Meetup #31
 
"Platform Engineering with Development Containers", Igor Fesenko
"Platform Engineering with Development Containers", Igor Fesenko"Platform Engineering with Development Containers", Igor Fesenko
"Platform Engineering with Development Containers", Igor Fesenko
 
Roundtable_-_API_Research__Testing_Tools.pdf
Roundtable_-_API_Research__Testing_Tools.pdfRoundtable_-_API_Research__Testing_Tools.pdf
Roundtable_-_API_Research__Testing_Tools.pdf
 
"Testing of Helm Charts or There and Back Again", Yura Rochniak
"Testing of Helm Charts or There and Back Again", Yura Rochniak"Testing of Helm Charts or There and Back Again", Yura Rochniak
"Testing of Helm Charts or There and Back Again", Yura Rochniak
 
LF Energy Webinar: Introduction to TROLIE
LF Energy Webinar: Introduction to TROLIELF Energy Webinar: Introduction to TROLIE
LF Energy Webinar: Introduction to TROLIE
 
"How we created an SRE team in Temabit as a part of FOZZY Group in conditions...
"How we created an SRE team in Temabit as a part of FOZZY Group in conditions..."How we created an SRE team in Temabit as a part of FOZZY Group in conditions...
"How we created an SRE team in Temabit as a part of FOZZY Group in conditions...
 
"AIRe - AI Reliability Engineering", Denys Vasyliev
"AIRe - AI Reliability Engineering", Denys Vasyliev"AIRe - AI Reliability Engineering", Denys Vasyliev
"AIRe - AI Reliability Engineering", Denys Vasyliev
 
Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...
Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...
Synergy in Leadership and Product Excellence: A Blueprint for Growth by CPO, ...
 
Are Human-generated Demonstrations Necessary for In-context Learning?
Are Human-generated Demonstrations Necessary for In-context Learning?Are Human-generated Demonstrations Necessary for In-context Learning?
Are Human-generated Demonstrations Necessary for In-context Learning?
 
How AI and ChatGPT are changing cybersecurity forever.pptx
How AI and ChatGPT are changing cybersecurity forever.pptxHow AI and ChatGPT are changing cybersecurity forever.pptx
How AI and ChatGPT are changing cybersecurity forever.pptx
 
How we think about an advisor tech stack
How we think about an advisor tech stackHow we think about an advisor tech stack
How we think about an advisor tech stack
 
ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...
ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...
ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...
 
"DevOps Practisting Platform on EKS with Karpenter autoscaling", Dmytro Kozhevin
"DevOps Practisting Platform on EKS with Karpenter autoscaling", Dmytro Kozhevin"DevOps Practisting Platform on EKS with Karpenter autoscaling", Dmytro Kozhevin
"DevOps Practisting Platform on EKS with Karpenter autoscaling", Dmytro Kozhevin
 
How to write an effective Cyber Incident Response Plan
How to write an effective Cyber Incident Response PlanHow to write an effective Cyber Incident Response Plan
How to write an effective Cyber Incident Response Plan
 
Enterprise Architecture As Strategy - Book Review
Enterprise Architecture As Strategy - Book ReviewEnterprise Architecture As Strategy - Book Review
Enterprise Architecture As Strategy - Book Review
 
Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...
Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...
Automation Ops Series: Session 1 - Introduction and setup DevOps for UiPath p...
 
Centralized TLS Certificates Management Using Vault PKI + Cert-Manager
Centralized TLS Certificates Management Using Vault PKI + Cert-ManagerCentralized TLS Certificates Management Using Vault PKI + Cert-Manager
Centralized TLS Certificates Management Using Vault PKI + Cert-Manager
 
The Future of Product, by Founder & CEO, Product School
The Future of Product, by Founder & CEO, Product SchoolThe Future of Product, by Founder & CEO, Product School
The Future of Product, by Founder & CEO, Product School
 
The Art of the Possible with Graph by Dr Jim Webber Neo4j.pptx
The Art of the Possible with Graph by Dr Jim Webber Neo4j.pptxThe Art of the Possible with Graph by Dr Jim Webber Neo4j.pptx
The Art of the Possible with Graph by Dr Jim Webber Neo4j.pptx
 
Relationship Counselling: From Disjointed Features to Product-First Thinking ...
Relationship Counselling: From Disjointed Features to Product-First Thinking ...Relationship Counselling: From Disjointed Features to Product-First Thinking ...
Relationship Counselling: From Disjointed Features to Product-First Thinking ...
 

Thrift vs Protocol Buffers vs Avro - Biased Comparison

  • 1. PB vs. Thrift vs. Avro Author: Igor Anishchenko Lohika - May, 2012
  • 2. Problem Statement Simple Distributed Architecture serialize deserialize deserialize serialize • Basic questions are: • What kind of protocol to use, and what data to transmit? • Efficient mechanism for storing and exchanging data • What to do with requests on the server side?
  • 3. …and you want to scale your servers... • When you grow beyond a simple architecture, you want.. • flexibility • ability to grow • latency • and of course - you want it to be simple
  • 4. How components talk • Database protocols - fine. • HTTP + maybe JSON/XML on the front - cool.
  • 5. How components talk • Database protocols - fine. • HTTP + maybe JSON/XML on the front - cool. • But most of the times you have internal APIs.
  • 6. Hasn't this been done before? (yes) • SOAP • CORBA • DCOM, COM+ • JSON, Plain Text, XML
  • 7. Should we pick up one of those? (no) • SOAP • XML, XML and more XML. Do we really need to parse so much XML? • CORBA • Amazing idea, horrible execution • Overdesigned and heavyweight • DCOM, COM+ • Embraced mainly in windows client software • HTTP/JSON/XML/Whatever • Okay, proven – hurray! • But lack protocol description. • You have to maintain both client and server code. • You still have to write your own wrapper to the protocol. • XML has high parsing overhead. • (relatively) expensive to process; large due to repeated tags
  • 8. Decision Time? As a developer - what are you looking for? Be patient, I have something for you on the subsequent slides!!
  • 9. High level goals! • Transparent interaction between multiple programming languages • A language and platform neutral way of serializing structured data for use in communications protocols, data storage etc.
  • 10. High level goals! • Transparent interaction between multiple programming languages • A language and platform neutral way of serializing structured data for use in communications protocols, data storage etc. • Maintain Right balance between: • Efficiency (how much time/space?) • Ease and speed of development • Availability of existing libraries and etc..
  • 11. Consideration: Protocol Space {"deposit_money": "12345678"} JSON Binary '0x6d', '0x6f', '0x6e', '0x01', '0xBC614E' '0x65', '0x79', '0x31', '0x32', '0x33', '0x34', '0x35', '0x36', '0x37', '0x38' Binary takes less space. No contest!
  • 12. Consideration: Protocol Time JSON Binary Push down automata No parser needed. The (PDA) parser (LL(1), binary representation IS LR(1)) -- 1 character [as close as to] the lookahead. Then, final machine representation. translation from characters to native types (int, float, etc) Binary is way faster. No contest
  • 13. Consideration: Protocol Ease of Use JSON Binary Brainless to learn Need to manually write Popular code to define message packets (total pain and error prone!!!) or Use a code generator like Thrift (oh noes, I don't want to learn something new!) Json is easier, binary is a pain.
  • 14. Several smart people have attacked this problem over the years and as a result there several good open source alternatives to choose from Here is where Data Interchange Protocols comes in play…
  • 15. Serialization Frameworks XML, JSON, Protocol Buffers, BERT, BSON, Apache Thrift, Message Pack, Etch, Hessian, ICE, Apache Avro, Custom Protocol...
  • 16. SF have some properties in common • Interface Description (IDL) • Performance • Versioning • Binary Format
  • 17. Protocol Buffer • Designed ~2001 because everything else wasn’t that good those days • Production, proprietary in Google from 2001-2008, open-sourced since 2008 • Battle tested, very stable, well trusted • Every time you hit a Google page, you're hitting several services and several PB code • PB is the glue to all Google services • Official support for four languages: C++, Java, Python, and JavaScript • Does have a lot of third-party support for other languages (of highly variable quality) • Current Version - protobuf-2.4.1 • BSD License
  • 18. Apache Thrift • Designed by an X-Googler in 2007 • Developed internally at Facebook, used extensively there • An open Apache project, hosted in Apache's Inkubator. • Aims to be the next-generation PB (e.g. more comprehensive features, more languages) • IDL syntax is slightly cleaner than PB. If you know one, then you know the other • Supports: C++, Java, Python, PHP, Ruby, Erlang, Perl, Haskell, C#, Cocoa, JavaScript, Node.js, Smalltalk, OCaml and Delphi and other languages • Offers a stack for RPC calls • Current Version - thrift-0.8.0 • Apache License 2.0
  • 19. Avro • I have a lot to say about Avro towards the end
  • 20. Typical Operation Model • The typical model of Thrift/Protobuf use is • Write down a bunch of struct-like message formats in an IDL- like language. • Run a tool to generate Java/C++/whatever boilerplate code. • Example: thrift --gen java MyProject.thrift • Outputs thousands of lines - but they remain fairly readable in most languages • Link against this boilerplate when you build your application. • DO NOT EDIT!
  • 21. Thrift Principle of Operation
  • 22. Interface Definition Language (IDL) • Web services interfaces are described using the Web Service Definition Language. Like SOAP, WSDL is a XML-based language. • The new frameworks use their own languages, that are not based on XML. • These new languages are very similar to the Interface Definition Language, known from CORBA.
  • 23. Thrift Protobuf namespace java serializers.thrift.media package serializers.protobuf.media; typedef i32 int option java_package = "serializers.protobuf.media"; typedef i64 long option java_outer_classname = "MediaContentHolder"; option optimize_for = SPEED; affects the C++ and Java enum Size { code generators SMALL = 0, LARGE = 1, message Image { } required string uri = 1; //url to the thumbnail enum Player { optional string title = 2; //used in the html JAVA = 0, required int32 width = 3; // of the image FLASH = 1, required int32 height = 4; // of the image } enum Size { SMALL = 0; struct Image { LARGE = 1; 1: string uri, //url to the images } 2: optional string title, required Size size = 5; 3: required int width, } 4: required int height, 5: required Size size, message Media { } required string uri = 1; optional string title = 2; struct Media { required int32 width = 3; 1: string uri, //url to the thumbnail required int32 height = 4; 2: optional string title, repeated string person = 5; 3: required int width, enum Player { 4: required int height, JAVA = 0; 5: required list<string> person, FLASH = 1; 6: required Player player, } 7: optional string copyright, required Player player = 6; } optional string copyright = 7; } struct MediaContent { 1: required list<Image> image, message MediaContent { 2: required Media media, repeated Image image = 1; } required Media media = 2; }
  • 24. Defining IDL Rules • Every field must have a unique, positive integer identifier ("= 1", " = 2" or " 1:", " 2:" ) • Fields may be marked as ’required’ or ’optional’ • structs/messages may contain other structs/messages • You may specify an optional "default" value for a field • Multiple structs/messages can be defined and referred to within the same .thrift/.proto file
  • 25. Tagging • The numbers are there for a reason! • The "= 1", " = 2" or " 1:", " 2:" markers on each element identify the unique "tag" that field uses in the binary encoding. • It is important that these tags do not change on either side • Tags with values in the range 1 through 15 take one byte to encode • Tags in the range 16 through 2047 take two bytes • Reserve the tags 1 through 15 for very frequently occurring message elements
  • 26. Java Example (Thrift example) // this file is BankDeposit.thrift struct BankDepositMsg { 1: required i32 user_id; 2: required double amount = 0.00; 3: required i64 datestamp;} ... import bank_example.BankDepositMsg; ... BankDepositMsg my_transaction = new BankDepositMsg(); my_transaction.setUser_id(123); my_transaction.setAmount(1000.00); my_transaction.setDatestamp(new Timestamp(date.getTime())); ... In Java (and other compiled languages) you have the getters and the setters, so that if the fields and types are erroneously changed the compiler will inform you of the mistake.
  • 27. The Comparison… Thrift Protocol Buffers Composite Type Struct {} Message {} Base Types bool bool byte 32/64-bit integers 16/32/64-bit integers float double double string string byte sequence Containers list<t1>: An ordered list of elements of type t1. No May contain duplicates. set<t1>: An unordered set of unique elements of type t1. map<t1,t2>: A map of strictly unique keys of type t1 to values of type t2. Enumerations Yes Yes Constants Yes No Example: const i32 INT_CONST = 1234; const map<string,string> MAP_CONST = {"hello": "world", "goodnight": "moon"} Exception Yes (exception keyword instead of the struct No Type/Handling keyword.)
  • 28. The Comparison Thrift Protocol Buffers License Apache BSD-style Compiler C++ C++ RPC Interfaces Yes Yes RPC Implementation Yes No (they do have one internally) Composite Type Extensions No Yes Data Versioning Yes Yes
  • 29. Performance • To keep things simple a lot is missing in the new frameworks. • For example the extensibility of XML or the splitting of metadata (header) and payload (body). • Of course the performance depends on the used operating system, programming language and the network. • Size Comparison • Runtime Performance
  • 30. Size Comparison Each write includes one Course object with 5 Person objects, and one Phone object. TBinaryProtocol – not optimized for space efficiency. Faster to process than the text protocol but more difficult to debug. TCompactProtocol – More compact binary format; typically more efficient to process as well Method Size (smaller is better) Thrift — TCompactProtocol 278 (not bad) Thrift — TBinaryProtocol 460 Protocol Buffers 250 (winner!) RMI 905 REST — JSON 559 REST — XML 836
  • 31. Runtime Performance • Test Scenario • Query the list of Course numbers. • Fetch the course for each course number. • This scenario is executed 10,000 times. The tests were run on the following systems: Operating System Ubuntu® CPU Intel® Core™ 2 T5500 @ 1.66 GHz Memory 2GiB Cores 2
  • 33. Runtime Performance Server CPU % Avg. Client CPU % Avg. Time REST — XML 12.00% 80.75% 05:27.45 REST — JSON 20.00% 75.00% 04:44.83 RMI 16.00% 46.50% 02:14.54 Protocol Buffers 30.00% 37.75% 01:19.48 Thrift — TBinaryProtocol 33.00% 21.00% 01:13.65 Thrift — TCompactProtocol 30.00% 22.50% 01:05.12
  • 34. Versioning • The system must be able to support reading of old data, as well as requests from out-of-date clients to new servers, and vice versa. • Versioning in Thrift and Protobuf is implemented via field identifiers. • The combination of this field identifiers and its type specifier is used to uniquely identify the field. • An a new compiling isn't necessary. • Statically typed systems like CORBA or RMI would require an update of all clients in this case.
  • 35. Forward and Backward Compatibility Case Analysis There are four cases in which version mismatches may occur: 1. Added field, old client, new server. 2. Removed field, old client, new server. 3. Added field, new client, old server. 4. Removed field, new client, old server.
  • 36. Forward and Backward Compatibility: Example 1 BankDepositMsg BankDepositMsg user_id: 123 user_id: 123 amount: 1000.00 amount: 1000.00 datestamp: 82912323 datestamp: 82912323 Producer (client) sends a message to a consumer (server). All good.
  • 37. Forward and Backward Compatibility: Example 2 BankDepositMsg BankDepositMsg user_id: 123 user_id: 123 amount: 1000.00 amount: 1000.00 datestamp: 82912323 datestamp: 82912323 branch_id: None Producer (old client) sends an old message to a consumer (new server). The new server recognizes that the field is not set, and implements default behavior for out-of-date requests… Still good
  • 38. Forward and Backward Compatibility: Example 3 BankDepositMsg BankDepositMsg user_id: 123 user_id: 123 amount: 1000.00 amount: 1000.00 datestamp: 82912323 datestamp: 82912323 branch_id: 1333 Producer (new client) sends a new message to an consumer (old server). The old server simply ignores it and processes as normal... Still good
  • 39. Serialization/deserialization performance are unlikely to be a decisive factor Thrift Protocol Buffers Richer feature set, but varies from Fewer features but robust Features language to language implementations Compare a protobuf Message It was open sourced by Facebook in April definition to a thrift struct definition Code Quality and 2007 probably to speed up development Design Compare the protobuf Java generator to and leverage the community’s efforts. the thrift Java generator Open mailing list Open-ness Apache project Code base and issue tracker Google still drives development Severely lacking, but catching up Documentation Excellent documentation Compare the protobuf documentation to the thrift wiki
  • 40. Projects Using Thrift • Applications, projects, and organizations using Thrift include: • Facebook • Cassandra project • Hadoop supports access to its HDFS API through Thrift bindings • HBase leverages Thrift for a cross-language API • Hypertable leverages Thrift for a cross-language API since v0.9.1.0a • LastFM • DoAT • ThriftDB • Scribe • Evernote uses Thrift for its public API. • Junkdepot
  • 41. Projects Using Protobuf • Google  • ActiveMQ uses the protobuf for Message store • Netty (protobuf-rpc) • I couldn’t find a complete list of protobuf users anywhere 
  • 42. Pros & Cons Thrift Protocol Buffers Slightly faster than Thrift when using "optimize_for = SPEED" More languages supported out of the box Serialized objects slightly smaller than Thrift due Richer data structures than Protobuf (e.g.: Pros Map and Set) to more aggressive data compression Better documentation Includes RPC implementation for services API a bit cleaner than Thrift Good examples are hard to find .proto can define services, but no RPC Cons implementation is defined (although stubs are Missing/incomplete documentation generated for you).
  • 43. I’d choose Protocol Buffers over Thrift, If: • You’re only using Java, C++ or Python. • Experimental support for other languages is being developed by third parties but are generally not considered ready for production use • You already have an RPC implementation • On-the-wire data size is crucial • The lack of any real documentation is scary to you
  • 44. I’d choose Thrift over Protocol Buffers, If: • Your language requirements are anything but Java, C++ or Python. • You need additional data structures like Map and Set • You want a full client/server RPC implementation built- in • You’re a good programmer that doesn’t need documentation or examples 
  • 45. Wait, what about Avro? • Avro is another very recent serialization system. • Avro relies on a schema-based system • When Avro data is read, the schema used when writing it is always present. • Avro data is always serialized with its schema. When Avro data is stored in a file, its schema is stored with it, so that files may be processed later by any program. • The schemas are equivalent to protocol buffers proto files, but they do not have to be generated. • The JSON format is used to declare the data structures. • Official support for four languages: Java, C, C++, C#, Python, Ruby • An RPC framework. • Apache License 2.0
  • 46. Avro IDL syntax is butt ugly and error prone // Avro IDL: { "type": "record", "name": "BankDepositMsg", "fields" : [ {"name": "user_id", "type": "int"}, {"name": "amount", "type": "double", "default": "0.00"}, {"name": "datestamp", "type": "long"} ] } // Same Thrift IDL: struct BankDepositMsg { 1: required i32 user_id; 2: required double amount = 0.00; 3: required i64 datestamp; }
  • 47. Comparison Avro Thrift and Protocol Buffer Dynamic schema Yes No Built into Hadoop Yes No Schema in JSON Yes No No need to compile Yes No No need to declare IDs Yes No Bleeding edge Yes No Sexy name  Yes No
  • 48. Specification • Schema represented in one of: • JSON string, naming a defined type. • JSON object of the form: • {"type": "typeName" ...attributes...} • JSON array • Primitive types: null, boolean, int, long, float, double, bytes, string • {"type": "string"} • Complex types: records, enums, arrays, maps, unions, fixed
  • 49. Comparison with other systems • Avro provides functionality similar to systems such as Thrift, Protocol Buffers, etc. • Dynamic typing: Avro does not require that code be generated. Data is always accompanied by a schema that permits full processing of that data without code generation, static datatypes, etc. • Untagged data: Since the schema is present when data is read, considerably less type information need be encoded with data, resulting in smaller serialization size. • No manually-assigned field IDs: When a schema changes, both the old and new schema are always present when processing data, so differences may be resolved symbolically, using field names.
  • 50. Avro Hands On Review • Q3 2012, I tested the latest Avro (1.6.3) • It throws you a message incompatible message when you change the field name • Serious bug, crashes w/ different versions of message (no fw/back compatibility). Emailed avro-dev@... • Documentation is nearly non-existent and no real users. Bleeding edge, little support
  • 51. Q&A

Editor's Notes

  1. Assigning TagsAs you can see, each field in the message definition has a unique numbered tag. These tags are used to identify your fields in themessage binary format, and should not be changed once your message type is in use. Note that tags with values in the range 1 through 15 take one byte to encode, including the identifying number and the field&apos;s type (you can find out more about this in Protocol Buffer Encoding). Tags in the range 16 through 2047 take two bytes. So you should reserve the tags 1 through 15 for very frequently occurring message elements. Remember to leave some room for frequently occurring elements that might be added in the future.