ElastiFlow vs. Filebeat and Logstash
Performance
The following results were obtained with the collectors running on a 16-core (AMD EPYC 7302P) server. The data was output to an Elasticsearch cluster consisting of seven data nodes, with three dedicated master nodes.
As much as possible given the options available, batch sizes and the # of workers were configured to comparable and optimal levels.
To provide a "full featured" comparison, the ElastiFlow Unified Flow Collector was tested with all enrichment features enabled. Logstash was tested with the legacy ElastiFlow 4.x pipeline to give it better feature parity. Filebeat relies on Elasticsearch ingest pipelines for anything beyond basic functionality. These pipelines were NOT used. This does give Filebeat a bit of an unfair advantage, however it was still many times slower despite its more favorable conditions.
Flows/second
Network Flow Data Support
Netflow
IPFIX
sFlow Flows
sFlow Counters
Broadcom IFA
IEs most recently added
SLA for supporting new vendors/devices
Platform Support
Elastic Stack
OpenSearch
Apache Kafka
Splunk
Cribl
ClickHouse/Grafana
Features
ECS schema support
CODEX schema support
Schema for IEs not covered by ECS
Properly handle Netflow v9/IPFIX Templates
Support Netflow v9/IPFIX Option Data
Translation ("subtype" handling) of IE values
GeoIP Enrichment
Autonomous System Enrichment
Reverse DNS IPs to hostname
User-defined IPs to hostname
User-defined Metadata for IPs
AS-based include/exclude for DNS resolutions and Metadata
IP Block include/exclude for DNS resolutions and Metadata
Obscure IP addresses and Hostnames
Threat Intelligence Enrichment
Microsoft 365 service enrichment
SalesForce service enrichment
Infer Client & Server sides of a conversation
Community ID support
Conversation ID support
User-defined Metadata for Interfaces
Translate Interface Index values to Interface Names
Translate AppIDs to Application names and attributes
User-defined Application names and attributes
Adjust Bytes/Packets based on Sample Rate
User-defined sample rates per flow exporter
Normalize timestamp values
Normalize percentage values
Normalize byte values
Configurable timestamp precision
* Must be done in an Elasticsearch Ingest Pipeline. This puts additional load on Elasticsearch, which is already the primary limiter of overall throughput.
** Can be achieved using a Logstash pipeline. This is not provided out of the box and must be developed and maintained.
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