Starcounter database

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Starcounter
NoSQL (NewSQL) database
Who am I?
● Bojan Brankov
o
PMF, Novi Sad 2000 - [redacted]
o
Levi9 Global Sourcing Balcan 2005 - 2012
 Java, .NET
o
Drey doo 2012 - 2014
 .NET
o
UZROK (entrepreneurship) 2014  .NET, Data Visualisations, multimedia, freelance
What is Starcounter?
●
●
●
●
●
In-memory Application Platform (NoSQL*)
Built in REST style Web server
Supports SQL queries
Fully ACID* compliant
Native .NET object API (C#, VB.NET,
Managed C++, etc.)
● .NET Framework 4.5
*Atomicity, Consistency, Isolation, Durability - Guarantee of database transactions reliability
Why are we talking about it?
● Let’s discuss modern databases!
Modern database Part 1
● Data processing is ubiquitous
● Over 150 special-purpose DBMS solutions
“a software system that uses a standard method of
cataloging, retrieving, and running queries on data.” 1970
● Often expensive huge server farms
● Compromises between extremes:
6 trade-offs
Modern database Part 2
● Trade-off #1: Human-Generated vs. Others
o
Building blocks upon building
blocks of data
o
Exclude scientific data
(Machine learning)
o
Focus on human-generated
(Everyday use application,
DBMS-friendly)
Modern database Part 3
● Trade-off #2: Structured vs. Unstructured
o
Unstructured - human-written part of the internet
(sequence of letters, word of natural language)
o
Structuredness - defined meaning in a certain
context (name value in CRM, business transactions)
o
Structured << Unstructured
o
eg. Amazon annual transactions 56Gb
Modern database Part 4
● Trade-off #3: Transactions vs. Analytics
o
Big Data phenomenon caused DBMS partitioning
o
OLTP - classic transactions, possible write conflicts
o
OLAP - static, read only, peak performance
o
Hybrid cutting-edge solutions (search engines, highfrequency trading) - “materialized aggregation”,
requires high performance transac. DBMS
Modern database Part 5
● Trade-off #4: In-memory vs. Disk-based
o
OLTP DBMS crucial for many evolving businesses
o
In 2005 RAM price dropped -> In-memory is a must!
o
Today modern servers come with 128GB of RAM
o
Disk-based databases still important for OLAP
o
In-memory DBMS still use disks (persistency and
reliability features)
Modern database Part 6
● Trade-off #5: Scale-in vs. Scale-out
o
Virtually - Consistent data vs. Inconsistent data
o
Scaling-out increases speed linearly with servers
o
System is in non-conflicted state all the time
o
Scaled-in systems keep transactional consistency
Modern database Part 7
● Trade-off #6: SQL vs. NoSQL
o
or “Classical” vs. “Modern”
o
From 2007 to 2012, the “classical” DBMS systems
with rich SQL-based syntax shifted to NoSQL DBMS
o
NoSQL - lightweight, cheap, fast but non-consistent
o
Now DBMS users demand rich syntax, operations
and basic OLAP
o
NoSQL + SQL = NewSQL
Modern database - Recap
1. Human-generated data
2. Structured (leave science to sciencers)
3. Transactional (OLTP with OLAP support)
4. In-memory with disc support
5. Scale-In and consistent
6. Modern, NewSQL
Alternatives
● OldSQL
+
●
+
-
Cca 10.000 transactions / seconds on a single machine
ACID guaranteed consistency
NoSQL
Distributed data, many more transactions per second
No consistency, no simplicity
● NewSQL
+ Millions of transactions per second on a single machine
+ ACID guaranteed consistency
Application of Starcounter?
● For modern applications: web, mobile services and
massive real time software (games, advertising…)
● Optimised for stellar concurrency and low latency
● Tight integration with HTTP, REST, JSON
● Simplicity to create view-models with zero glue code
(VMMV, VMC)
● Uses integration with WPF and XAML for flexible
desktop applications
How does it work?
● VMDBMS
+ ?? => PROFIT
o
Integration between application runtime VM and the
data management system (just like CLR or Java
VM)
o
Data in one single place in RAM all the time
o
Direct access: No temporary copies, no serialization
and deserialization
o
Uses disks to secure the transaction log and a
checkpointed database image
Why is that good?
● Fundamental criteria: Moving both the model
and controller logic inside the db => less
strain on db
● Moving memory around is a bottleneck!
● Clock cycles for business logic << Clock
cycles for communicating and moving data
Starcounter database Part 1
● Do not think relational!
● Classes are tables and instances are rows
● Database objects live in the database from
the beginning (new operator)
using Starcounter;
[Database]
public class Persistent {
public string Name;
}
Starcounter database Part 2
● Public fields, public auto-created properties
and public properties getting and setting
private fields are columns
using Starcounter;
[Database]
public class Person {
public string FirstName;
public string LastName { get; set; }
public string FullName { get { return FirstName + " " + LastName; } }
}
Starcounter database Part 3
● Offers relational, graph, object oriented and
document access, all rolled into one.
● Relations are established through object
references rather than explicit keys
[Database]
public class Quote {
public Person Who;
private string _Text;
public string Text { get { return _Text; } set { _Text = value; } }
}
Starcounter database Part 4
● The Database attribute is inherited from
base to subclasses
o
Any class that directly or indirectly inherits a class
with the Database attribute implicitly becomes a
database class
[Database]
public class Vehicle {
public int YearOfManufacturing;
}
public class Car : Vehicle {
public int Wheels;
}
Starcounter database Part 5
● Every Database class is available to
standard SQL expressions in C#, no ORM
o
You can use queries with path expressions to
increase performance and replace complex joins
[Database]
..person.City.Name =?”, this);
public class Person{
public String Name;
public IEnumerable Quotes(){
return SQL(”SELECT q FROM Quotes q WHERE q.Who=?”, this);
}
Starcounter database Part 6
● You can exclude fields and auto-created
properties from becoming columns by using
the Transient custom attribute.
o
It will remain a regular .NET field/property -> value
stored on the CLR heap and garbage collected
● Row is removed using Delete() method.
Starcounter database Part 7
● Starcounter supports:
o
Transaction scopes
o
Long running transactions
o
Nested transactions
o
Parallel transactions
Starcounter database - Recap
● STARCOUNTER
class definition
new() operator
= operator
SQL(String)
Delete() method
●
SQL
CREATE TABLE
INSERT
UPDATE
SELECT
DELETE
Is that all?
● Integrated Communication Server
o
Extremely fast gateway
o
Handles ≈1M HTTP requests per second
o
Serves REST, MVVM, MVC code, business logic
and database transactions
o
Can communicate using REST and JSON, through
mirrored MVVM, perfect for Web Component
frameworks (AngularJS)
What about the performances?
500k ACID read-only
transactions per second
per core
Scales with number of
cores almost linearly
100k ACID read-write
transactions per second
per core, to maximum of
300k on 4 cores
1.5M clients
0.5M accounts
5% transfers, 95% reads
XEON E5 (10 cores),
128GB RAM and SSD
How much does it cost?
● Cost projection for mid
size ERP system
● MySQL solutions still
require powerful
hardware or even server
farm
● SC runned complete
system on a single lap
top
Any other questions?
● I thought so!
[email protected]
[email protected]
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