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Performance and Feature Comparison
on InfiniFlux, MySQL, MongoDB,
Splunk, and Elasticsearch
www.infiniflux.com
Feature - Query Language
2
Product Query Language
InfiniFlux Easy to process statistics as it supports standard SQL
MySQL Easy to process statistics as it supports standard SQL
Elasticsearch Require to enter conditional clauses of SQL queries in the REST API and JSON format
MongoDB Difficult to use it since it requires to enter conditional clauses in the โ€œFindโ€ method
Splunk Easy to process statistics as it supports search processing language (SPL)
Conclusion
Easy and efficient to process unstructured big data with Splunk or Elasticsearch, and
structured big data with Infiniflux which supports SQL.
For statistical processing, difficult to use Elasticsearch and MongoDB due to
complicated query.
Feature - Time Series Query
3
Product Time Series Query
InfiniFlux
Use โ€œDURATIONโ€ clause and hidden column, โ€œ_ARRIVAL_TIMEโ€.
Able to process high-speed query as input data are partitioned based on
input time.
MySQL Not supported
Elasticsearch Not supported
MongoDB Not supported
Splunk Possible to use โ€œDURATIONโ€ clause for searching
For time series query, InfiniFlux and Splunk are easy and efficient to use.
In terms of search performance, InfiniFlux is the best for searching time series data.
Conclusion
Feature - Full Text Search
4
Product Full Text Search
InfiniFlux
Able to search by using โ€œSEARCHโ€ operator.
Able to search data at a high-speed by using the inverted index.
MySQL
Use โ€œLIKEโ€ operator.
It may not able to use index based on search patterns, and as a result, slow down in search
speed.
Elasticsearch Supported
MongoDB Supported
Splunk Supported
InfiniFlux is the only available DBMS for full text search at a high-speed against
structured data.
Conclusion
Feature - Extended Data Type
5
Product Extended Data Type
InfiniFlux Support IPv6 and IPv4 types, and operators (contains and contained)
MySQL Not supported
Elastic search Not supported
MongoDB Not supported
Splunk Support functions such as โ€œcidrmatchโ€
Conclusion
InfiniFlux is the only available DBMS for supporting network data type and related
functions.
6
Field
Time of log
creation
Source IP
Source
port
Destination
IP
Destination
port
Protocol
type
Log text Status code Data size
Field Name arrivaltime srcip srcport dstip dstport protocol eventlog eventcode eventsize
Field Type datetime ipv4 integer ipv4 integer short
varchar
(1024)
short long
Evaluate data input and analyze performance of each product by 100,000,000 records
(13GB) on basic hardware environment
Hardware
Specifications
- CentOS 6.6
- Intel(R) Core(TM) i7-4790
CPU @ 3.60GHz (4 core)
- 32GB Memory
- SATA DISK
Test
Targets
- InfiniFlux 2.0
- MySQL 5.2
- Splunk 6.2.3
- Elasticsearch 1.5.3
- MongoDB 3.0.3
[DATA]
Performance
7
4334
13848
698
1624
389
0 2000 4000 6000 8000 10000 12000 14000 16000
Elasticsearch
MySQL
Splunk
MongoDB
INFINIFLUX
DATA LOADING TIME (sec)
Performance
Conclusion
InfiniFlux ables to load 100,000,000 data records only within 389 seconds, the fastest time ever
among the competitors.
8
3
1
85
208
4
0 50 100 150 200 250
Elasticsearch
MySQL
Splunk
MongoDB
INFINIFLUX
COMPLEX SEARCH (sec)
Performance
Conclusion
InfiniFlux only takes 4 seconds to perform composite operations.
MySQL takes a second to search, which is the fastest, however, it takes a long time to load data.
9
4337
13849
783
1832
393
Elasticsearch
MySQL
Splunk
MongoDB
INFINIFLUX
OVERALL RESULT (sec)
Performance
Conclusion
Overall, InfiniFlux ables to conduct 100,000,000 records of data input and composite operations
only within 393 seconds.
10
Performance
20.4
17.52
21.6
42.11
4.1
0 5 10 15 20 25 30 35 40 45
Elasticsearch
MySQL
Splunk
MongoDB
INFINIFLUX
STORAGE SIZE (GB)
Conclusion InfiniFlux can compress 13GB of data including indices into 4.1GB showing compression rate of
68.5%.
Source size
11
Performance
InfiniFlux MongoDB Splunk MySQL Elasticsearch
Duration (sec) 389 (00:06:29) 1624 (00:10:16) 698 (00:11:38) 13848 (03:50:48) 4334 (01:12:14)
Inserted csv size (GB) 13G
Data size (GB) 4.1G 42.1157G 8.6G 17.52G 20.4G
Compression ratio (%) 76.92%
Decompressed
(223.97%)
33.95%
Decompressed
(130.77%)
Decompressed
(156.92%)
Memory usage (%) 29.22 73.75 40.78 87.59 89.82
Memory usage (GB) 9.0756 22.9073 12.667 27.20 27.8965
Data search
Search Text (2.6M) 2s 213s (00:03:33) 424s (00:07:04) 31s 2s
IP search (2.66M) 1s 212s (00:03:32) 40s 1s 3s
Time search <1s 211s (00:03:31) 8s 1s 2s
Statistic
Sum 25s 217s (00:03:37) 435s (00:07:15) 35s 1s
Average 25s 219s (00:03:39) 436s (00:07:16) 46s 4s
Count 17s 218s (00:03:38) 382s (00:06:22) 45s 3s
Complex query 4s 208s 85s 1s 3s
OVERALL RESULT 393s 1832s 783s 13849s 4337s
*For more information on the results, please visit: http://www.infiniflux.com/performance
The World's Fastest
Time Series DBMS
for IoT and Big Data
www.infiniflux.com
info@infiniflux.com
InfiniFlux

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IniniFlux Feature_Perf_Comparison

  • 1. Performance and Feature Comparison on InfiniFlux, MySQL, MongoDB, Splunk, and Elasticsearch www.infiniflux.com
  • 2. Feature - Query Language 2 Product Query Language InfiniFlux Easy to process statistics as it supports standard SQL MySQL Easy to process statistics as it supports standard SQL Elasticsearch Require to enter conditional clauses of SQL queries in the REST API and JSON format MongoDB Difficult to use it since it requires to enter conditional clauses in the โ€œFindโ€ method Splunk Easy to process statistics as it supports search processing language (SPL) Conclusion Easy and efficient to process unstructured big data with Splunk or Elasticsearch, and structured big data with Infiniflux which supports SQL. For statistical processing, difficult to use Elasticsearch and MongoDB due to complicated query.
  • 3. Feature - Time Series Query 3 Product Time Series Query InfiniFlux Use โ€œDURATIONโ€ clause and hidden column, โ€œ_ARRIVAL_TIMEโ€. Able to process high-speed query as input data are partitioned based on input time. MySQL Not supported Elasticsearch Not supported MongoDB Not supported Splunk Possible to use โ€œDURATIONโ€ clause for searching For time series query, InfiniFlux and Splunk are easy and efficient to use. In terms of search performance, InfiniFlux is the best for searching time series data. Conclusion
  • 4. Feature - Full Text Search 4 Product Full Text Search InfiniFlux Able to search by using โ€œSEARCHโ€ operator. Able to search data at a high-speed by using the inverted index. MySQL Use โ€œLIKEโ€ operator. It may not able to use index based on search patterns, and as a result, slow down in search speed. Elasticsearch Supported MongoDB Supported Splunk Supported InfiniFlux is the only available DBMS for full text search at a high-speed against structured data. Conclusion
  • 5. Feature - Extended Data Type 5 Product Extended Data Type InfiniFlux Support IPv6 and IPv4 types, and operators (contains and contained) MySQL Not supported Elastic search Not supported MongoDB Not supported Splunk Support functions such as โ€œcidrmatchโ€ Conclusion InfiniFlux is the only available DBMS for supporting network data type and related functions.
  • 6. 6 Field Time of log creation Source IP Source port Destination IP Destination port Protocol type Log text Status code Data size Field Name arrivaltime srcip srcport dstip dstport protocol eventlog eventcode eventsize Field Type datetime ipv4 integer ipv4 integer short varchar (1024) short long Evaluate data input and analyze performance of each product by 100,000,000 records (13GB) on basic hardware environment Hardware Specifications - CentOS 6.6 - Intel(R) Core(TM) i7-4790 CPU @ 3.60GHz (4 core) - 32GB Memory - SATA DISK Test Targets - InfiniFlux 2.0 - MySQL 5.2 - Splunk 6.2.3 - Elasticsearch 1.5.3 - MongoDB 3.0.3 [DATA] Performance
  • 7. 7 4334 13848 698 1624 389 0 2000 4000 6000 8000 10000 12000 14000 16000 Elasticsearch MySQL Splunk MongoDB INFINIFLUX DATA LOADING TIME (sec) Performance Conclusion InfiniFlux ables to load 100,000,000 data records only within 389 seconds, the fastest time ever among the competitors.
  • 8. 8 3 1 85 208 4 0 50 100 150 200 250 Elasticsearch MySQL Splunk MongoDB INFINIFLUX COMPLEX SEARCH (sec) Performance Conclusion InfiniFlux only takes 4 seconds to perform composite operations. MySQL takes a second to search, which is the fastest, however, it takes a long time to load data.
  • 9. 9 4337 13849 783 1832 393 Elasticsearch MySQL Splunk MongoDB INFINIFLUX OVERALL RESULT (sec) Performance Conclusion Overall, InfiniFlux ables to conduct 100,000,000 records of data input and composite operations only within 393 seconds.
  • 10. 10 Performance 20.4 17.52 21.6 42.11 4.1 0 5 10 15 20 25 30 35 40 45 Elasticsearch MySQL Splunk MongoDB INFINIFLUX STORAGE SIZE (GB) Conclusion InfiniFlux can compress 13GB of data including indices into 4.1GB showing compression rate of 68.5%. Source size
  • 11. 11 Performance InfiniFlux MongoDB Splunk MySQL Elasticsearch Duration (sec) 389 (00:06:29) 1624 (00:10:16) 698 (00:11:38) 13848 (03:50:48) 4334 (01:12:14) Inserted csv size (GB) 13G Data size (GB) 4.1G 42.1157G 8.6G 17.52G 20.4G Compression ratio (%) 76.92% Decompressed (223.97%) 33.95% Decompressed (130.77%) Decompressed (156.92%) Memory usage (%) 29.22 73.75 40.78 87.59 89.82 Memory usage (GB) 9.0756 22.9073 12.667 27.20 27.8965 Data search Search Text (2.6M) 2s 213s (00:03:33) 424s (00:07:04) 31s 2s IP search (2.66M) 1s 212s (00:03:32) 40s 1s 3s Time search <1s 211s (00:03:31) 8s 1s 2s Statistic Sum 25s 217s (00:03:37) 435s (00:07:15) 35s 1s Average 25s 219s (00:03:39) 436s (00:07:16) 46s 4s Count 17s 218s (00:03:38) 382s (00:06:22) 45s 3s Complex query 4s 208s 85s 1s 3s OVERALL RESULT 393s 1832s 783s 13849s 4337s *For more information on the results, please visit: http://www.infiniflux.com/performance
  • 12. The World's Fastest Time Series DBMS for IoT and Big Data www.infiniflux.com info@infiniflux.com InfiniFlux