1. AND
Products
comparison

2. Technical overview
Programming language C++ Java
Language Bindings & Clients C, C++, Erlang, Haskell, Java, JavaScript, .NE Java, Jython ,Groovy DSL , Scala, REST
T (C#
F#, PowerShell, etc), Perl, PHP, Python, Rub
y, Scala.
Protocols Mongo Wire Protocol Apache Avro, Thrift, REST
First public release and current state Feb 2009 Last release 2.0.2 14th Jul 2010 Last release 0.92.0 23th January
December 2011 2012

3. Technical overview
Querying Mongo Query Language Filter Language
Atomicity Conditional +
Consistency + +
Isolation - +
Durability + -
Periodic-Update Secondary Index
Indexing of embedded element, Filter Query
Secondary Indexes
compound key Dual-Write Secondary Index
Summary Tables
Map/Reduce Supports
Sharding + +
Replication + +
Revision control - +

4. MongoDB features
Document-oriented
Capped Collections
Greed FS
Indexing
Map Reduce
Query language
JSON/BSON
Eventually-consistence

5. HBase features
• Column oriented(after Google big table)
• Bloom filters on per column basis
• MapReduce
• Secondary Indexes
• HDFS based
• Revision controll

6. MongoDB configuration
example

8. HBase configuration

9. MongoDB use cases
Git Hub : the social coding site, is using MongoDB
for an internal reporting application.
РосГос затраты: RosSpending is the first Russian
public spending monitoring project..
Disney: common set of tools and APIs for all games
within the Interactive Media Group, using
MongoDB as a common object repository to persist
state information.
Over 300 of companies have prodact deployments
of mongoDB

10. HBase use cases
Facebook : Real-Time messaging
Over 152 billions messages monthly
Adobe: 30 nodes social services ,data and
processing for internal use.
Explorys: over a billion anonymized clinical
records
Mozilla Socorro : Crash reporting system
Powered by about 40 companies

11. Benchmarking
• Enveroment: Amazon Elastic compute cloud.
• Testing tool – Yahoo Cloud Service
benchmark(YCSB)

12. 2000.00
4000.00
6000.00
8000.00
10000.00
12000.00
0.00
0
1200
2400
3600
4800
6000
7200
8400
9600
10800
12000
13200
14400
15600
16800
18000
19200
20400
12hours of loading.
21600
22800
24000
25200
167.600.000 for 4 shards
26400
27600
28800
30000
31200
32400
95.000.000 records for 2 shards
33600
34800
36000
37200
38400
MongoDB Benchmarking.
39600
40800
2 shards loading
4 shards loading
42000
43200
44400

13. 50% reads 50% updates
12000
10000
8000
2 shards update
2 shards read
6000
4 shards update
4 shards read
4000
2000
0
500 1000 2000 3000 3300 5000

14. 95% reads 5% updates
16000
14000
12000
10000 2 shards update
8000 2 shards read
4 shards update
6000
4 shards read
4000
2000
0
500 1000 2000 3000 4000 5000

15. Read only performance
10000
9000
8000
7000
6000
5000 2 shards
4000 4 shards
3000
2000
1000
0
500 1000 2000 3000 4000 5000

16. Read Insert performance
250000
200000
150000 2 shards insert
2 shards read
100000 4 shards insert
4 shards read
50000
0
200 300 400

17. Questions
skype: google_mic
mailto: mikhail.hul@gmail.com
mailto: mikhail.hul@altoros.com