Thursday, May 15, 2014

Write Operation: MongoDB Vs PostgreSQL 9.3 (JSON)

PostgreSQL 9.3 has lot of new improvement like the addition of new operators for JSON data type in postgreSQL, that prompted me to explore its features for NoSQL capabilities.

MongoDB is one of NoSQL solutions that have gotten a great deal of attention in the NoSQL market. So, this time I thought to do some benchmarking with the NoSQL capability of JSON in MongoDB and the JSON datatype in PostgreSQL 9.3

For this benchmark, I have used the same machine with no optimization in installation of PostgreSQL and MongoDB (since I wanted to see how things work, out of box with default installation). And I used the sample data from MongoDB's site, around which I had developed the functions which can generate random data using the same sample for Mongo and for PostgreSQL.

In this benchmarking, I have verified following:
1. PostgreSQL COPY Vs Mongo-Import
2. Data Disk Size of PostgreSQL and Mongo for same amount of data.
3. PostgreSQL INSERT Vs Mongo Insert

Some specification before I would display the result:
1. Operating System: CentOS 6.5, 64 bit.
2. Total Memory: 1.538 GB
3. MongoDB version: 2.4.9
4. PostgreSQL: 9.3

Below is the results which I have got:

For Bulkload (COPY Vs MongoImport):
# of rows            1000               10000         100000          1000000
mongo-import (ms)    86.241679          569.761325      6940.837053   68610.69793
PG COPY (ms)         27.36344           176.705094      1769.641917   24801.23291

Disk space utilization:

# of rows           1000        10000         100000         1000000
mongo disks (mb)    208         208           208.2033236    976
pg size (mb)     0.3515625      3.2890625     32.71875       326.8984375


# of Inserts         1000         10000         100000         1000000
MONGO INSERTS (sec)  0.521397404  4.578372454   43.92753611    449.4023542
PG INSERTS (sec)     0.326254529  4.169742939   32.21799302    319.2562722

If you look at above stats, you can see PostgreSQL JSON is much better in bulk loading and INSERTs.

Best thing is that it takes less space than MongoDB and doesn't eat up much disk space.

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