An Explosion of Databases

Adam Retter

adam@evolvedbinary.com
@adamretter

The XML Summer School
Oxford 12/09/2018

Adam Retter

  • eXist-db - Core Developer (13 years!)

    • Native XML Database

    • Implemented in Java

    • Open Source: LGPL v2.1

  • RocksDB - Developer (4 years)

    • Key / Value Database

    • Implemented in C++ (and Java API)

    • Open Source: GPL v2 / Apache 2.0

  • Granite - Developer (4 years)

    • Polystore: XML, Key/Value (JSON, MarkDown... DOM)

    • Implemented in C++ and Java

    • Will be Open Source: likely AGPL v3

In the beginning... ~1960s

  • General Electric - IDS (Integrated Data Store)

    • Possibly the first DBMS

    • Network Model

    • Schema

    • CODASYL

    • Tuple-at-a-time queries

  • IBM - IMS (Information Management System)

    • Developed for the Apollo moon mission (purchasing)

    • Hierarchical Model

    • Programmer defined physical storage (Hash / Tree / etc.)

      • Determines the API you can use to query

    • Tuple-at-a-time queries

Things Start Improving... ~1970s

  • Ted Codd (IBM)

    • Avoid rewritting applications for every schema change

    • Need more abstraction

      • Logical vs. Physical

      • Let the database engine worry about physical storage

      • Let the user query their logical model

      • Query through a high-level language

    • The Relational Data Model is born

  • Implementations

    • System R (Jm Gray - IBM)

    • INGRES (Michael Stonebraker - U.C. Berkeley)

    • Oracle (Larry Ellison)

Things Stabilise... ~1980s

  • Mostly Improvements to the Relational Model

  • SQL is The standard - 1986 ANSI

  • Further notable implementations:

    • Informix (1981 / SQL 1985)

    • IBM DB2 (1983)

    • Sybase (1987)

      • Partnership created Microsoft SQL Server (1989)

      • Later SAP!

    • Postgres (1989)

      • Stonebraker - Post-Ingres

  • Oracle dominates!

  • New: Object Database (1985) / Object-Relational hybrids

Kinda dull, until... ~1990s

  • Postgres95 (1995)

    • 1994 - Berkley shutters Postgres

    • Released as Open Source under MIT

    • Forked as Postgres95 (later PostgreSQL)

  • MySQL (1995)

    • Open Source rewrite of mSQL

  • The Web Takes off!

    • The rise of the LAMP stack!

    • 1995 - 16 million users (0.4% world pop.)

    • 1999 - 248 million users (4.1% world pop.)

  • Cap Theorem (Eric Brewer - 1999)

Scaling... ~2000s

  • SQLLite (2000)

  • The Web (2009)

    • Reaches 1,802 million users (26.6% world pop.)

  • Big Web Companies:

    • Commercial databases are too expensive and don't scale

    • Open Source databases lack features

    • Each building middle-ware to distribute load, e.g.:

      • eBay and Amazon - Oracle

      • Facebook - MySQL

    • Start building their own DBMS:

      • Google - BigTable/LevelDB (2004), Spanner (2012)

      • Amazon - DynamoDB (2012)

The explosion... ~2010s

  • Much data!

    • Facebook - 6 billion photos a month / 100 petabytes (2012)

    • Google - 40,000 searches per second (2014)

  • The NoSQL "Movement"

    • Not SQL => Not (only) SQL

    • Rejects classic DMBS in favour of lighter faster storage

    • Compromises - Consistency, Availability, Durability vs. Performance

    • Full-circle. The SQL vendors fought back! - NewSQL

  • New Hardware

    • RAM is cheap

    • SSD / NVMe / RDMA

    • GPU and FPGA

Interesting databases today

  • RocksDB

    • Facebook's Open Source LevelDB fork... for SSD/NVMe etc.

    • Key/Value

    • Powers almost everything at Facebook (and others)

    • Used in: ArangoDB, Cassandra, CockRoach DB, MongoRocks (MongoDB), MyRocks (MySQL), many more...

  • MapD

    • Database core is in-memory and GPU optimized

    • SQL

    • Optimized for data analytics

  • CockrochDB

    • Open Source. Distributed database.

    • SQL

  • ScyllaDB

    • Cassandra compatible implementation in C++

    • Column Store

    • 2x - 10x faster than Cassandra

    • Optimised for multi-threaded machines. Clustering also.

  • FoundationDB

    • Previously closed source, now Open Source (under Apple)

    • Key/Value Store

    • Designed for performance (after durability)

    • Compromises - Transaction lifetime

  • FasterDB

    • Microsoft Open Source

    • Embedded key/value store

    • Impressive performance "claims"

Where are we heading?

  • In-Memory?

    • Memory / Persistent disk is now blurred (NVMe etc).

    • Custom Hardware - ASIC, FPGA, RDMA Network etc.

  • Consistency is back in vogue.

  • Likely SQL (or similar) for the user.

  • Distributed. Sharding. Clustered.

    • Node failure happens! Data centre failure happens!

  • Common Core, e.g.: RocksDB.

  • Polystore vs. Multiple databases

Questions?

Learn More:
CMU Advanced Database Systems
https://15721.courses.cs.cmu.edu/spring2018/
...The YouTube Videos are excellent!

An Explosion in Databases

By Adam Retter

An Explosion in Databases

Talk given on Trends and Transients at The XML Summer School 2018, Oxford

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