2016 English 34 slides 6394 views
Why we love ArangoDB. The hunt for the right NosQL Database
The document discusses the advantages of NoSQL databases compared to traditional relational databases, emphasizing their flexibility and suitability for various use cases. It explores different categories of NoSQL databases, challenges posed by cloud computing and big data, and the implications of the CAP theorem. Additionally, it highlights the author's search for a multifunctional NoSQL solution with a focus on ArangoDB, detailing its features, capabilities, and community support.
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1
The hunt for the right
NoSQL database
Andreas Jung
@MacYET
info@zopyx.com • www.zopyx.de
Why we ♥
2
Why we ♥
/about
• Python developer since 1993
• Freelancer since 2004
• Python, Zope, Plone …
• individual software development
• Electronic Publishing
(Publishing workflows DOCX→XML→PDF | EPUB | HTML,
XML consulting)
• Founded publishing projects
• XML-Director
• Produce & Publish
3
Why we ♥
Disclaimer
• This talk is completely
• biased
• opinionated
• unscientific
• not affiliated with ArangoDB GmbH
4
Why we ♥
Relational databases
• well understood
• common data model
• long history:
• System R (1974)
• Oracle (1979)
• Structured Query Language (Standards: ISO/IEC 9075 + 13249)
• theoratically interoperable if you stick to the SQL standard
5
Why we ♥
NoSQL = not SQL
6
Why we ♥
NoSQL = non-relational
7
Why we ♥
“NoSQL is not about performance, scaling, dropping
ACID or hating SQL — it is about choice. As NoSQL
databases are somewhat different it does not help very
much to compare the databases by their throughput and
chose the one which is faster. Instead—the user should
carefully think about his overall requirements and
weight the different aspects. Massively scalable key/value
stores or memory-only systems can archive much higher
benchmarks. But your aim is to provide a much more
convenient system for a broader range of use-cases—
which is fast enough for almost all cases.”
Jan Lenhardt (CouchDB)
8
Why we ♥
Categories of NoSQL databases
• Key-Value
• Memcached, Redis, Riak, …
• Column-oriented
• Cassandra, …
• Document (JSON)
• MongoDB, CouchDB, …
• Tabular
• Big Table, Hase, …
• Graph
• Neo4J, …
• XML, Object…
• eXist, BaseX, Marclogic, ZODB, … http://martinfowler.com/articles/nosqlKeyPoints.html
https://www.youtube.com/watch?v=qI_g07C_Q5I
9
Why we ♥
New challenges
• Cloud
• Replication
• massive data explosion: „Big Data“
• Globally distributed systems
• Specialized requirements
➡ more specialized databases
➡ Relational databases are no longer the only option
10
Why we ♥
CAP Theorem
It is impossible for a distributed computer system
to simultaneously provide all three of the following
guarantees:
• Consistency
(every read receives the most recent write or an
error)
• Availability
(every request receives a response, without
guarantee that it contains the most recent
version of the information)
• Partition tolerance
(the system continues to operate despite
arbitrary partitioning due to network failures)
(Eric Brewer)
PICK TWO
11
Why we ♥
My personal hunt for a multi-purpose
NoSQL database …
• Should fit most mid-size projects
• Document store (+ graphs)
• Arbitary query options
• Cross-table/collection relationships
• (optional) transactional integrity (ACID)
across multiple documents and operations
• replication/clustering
12
Why we ♥
My personal hunt…
…and various others
13
Why we ♥
My personal hunt…
…and various others
14
Why we ♥
bought in 2015 by
15
Why we ♥
The high-end $$$$ solution
• the most professional, feature-complete,
feature-rich NoSQL database ever
• document (XML/JSON) store and graph database
• focus on data integration and data consolidation
• expensive but worth the money if you need the features
• widely used in enterprises
(saved „Obama-Care“ project)
16
Why we ♥
A native multi-model database
• Document store (JSON)
• JOINs, secondary indexes, ACID transactions
• Key-value store
• Graph database
• integrates with document store
• rich graph query operations
• nodes and edges can contain complex data
➡ all models can be combined
17
Why we ♥
Foxx framework
• implement your own REST micro-services directly with
Javascript running inside ArangoDB
• unified data storage logic (decouples API from external services)
• reduced network overhead (no network latencies)
• you can use the full JS Stack
• batteries included
• build-in job queue
18
Why we ♥
AQL - One Query Language to rule them all
• AQL = Arango Query Language
• declarative, human-readable DSL (I hate JSON queries)
• document queries, graph queries, joins, all combined in
one statement
• ACID support with multi-collection transactions
• easy to understand with some SQL background
19
Why we ♥
20
Why we ♥
21
Why we ♥
22
Why we ♥
23
Why we ♥
24
Why we ♥
25
Why we ♥
• Agency (high-avail
resilient key/value store,
Raft Consensus Protocol)
• Coordinators
• Primary DB servers
• Secondaries
• Asynchronous/
synchronous replication
with automatic fail-over
Custering, replication, sharding
26
Why we ♥
Benchmark (against ArangoDB V 2)
https://www.arangodb.com/2015/10/benchmark-postgresql-mongodb-arangodb/
27
Why we ♥
Benchmark (against ArangoDB V 2)
https://www.arangodb.com/2015/10/benchmark-postgresql-mongodb-arangodb/
Neighbour search Shortest path
28
Why we ♥
Python bindings (PyArango)
29
Why we ♥
Python bindings (PyArango)
Query (AQL)
Query (by example)
30
Why we ♥
Graphs
31
Why we ♥
Deployment & operations
32
Why we ♥
Misc
• current version 3.0, (3.1 RC3)
• good documentation
• regular updates and fixes
• nicely supported
• supported by ArangoDB GmbH in Cologne
33
Why we ♥
• Community Edition (Apache License 2.0)
• Enterprise Edition (SLA, support options,
smart graphs, auditing, better security control)
https://www.arangodb.com/why-arangodb/references/https://www.arangodb.com/arangodb-drivers/
34
Why we ♥
Questions?