What is Gravwell?
It is the most flexible full-stack analytics platform in the world. We excel at fusing disparate data sources such as firewall logs, end point event logs, network traffic, OT IDS logs, OT process data, threat feed data, etc. to create a central source of knowledge. Created in the IoT age we know modern data insights demand unlimited ingest and analysis capability for cybersecurity, IoT, business analytics, and more. We support a wide range of customers, from energy production, energy delivery, government, finance, and insurance to health and beauty products.
Gravwell is a tool in the Log Management category of a tech stack.
Who uses Gravwell?
Developers
4 developers on StackShare have stated that they use Gravwell.
Pros of Gravwell
1
1
1
1
1
1
1
1
1
1
1
Gravwell's Features
- Ability for deployment in cloud, on-premises, or in an isolated on-premises network lacking outside network connectivity
- Capable of collecting disparate unstructured time-series data sources into a queryable data lake
- Enable data scientists to create custom analysis code/tools to be executed as part of a search pipeline or query system
- Analysts and data scientists have access to raw entry records for retroactive analysis and application of machine learning that did not exist at the time of collection
- Capable of data separation and fine-grained access controls for multi-tenancy
- Data collectors or agents are modifiable by the customer to enable processing, filtering, or enrichment before forwarding to the central store
- Massive scalability. Over 100 Terabytes a day is no problem.
- Unlimited data ingestion
- Unlimited retention
- Live Dashboards
- Secure and Proprietary
- Offline ("Cold") and online ("Hot") replication
- Region-aware redundancy
- Multi-tenancy Permissions & Unlimited user seats
- Binary data support
- Configurable data retention and automatic age-out
- Distributed web frontends
- Unlimited search count
Gravwell Alternatives & Comparisons
What are some alternatives to Gravwell?
Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
Logstash
Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.
SLF4J
It is a simple Logging Facade for Java (SLF4J) serves as a simple facade or abstraction for various logging frameworks allowing the end user to plug in the desired logging framework at deployment time.
Logback
It is intended as a successor to the popular log4j project. It is divided into three modules, logback-core, logback-classic and logback-access. The logback-core module lays the groundwork for the other two modules, logback-classic natively implements the SLF4J API so that you can readily switch back and forth between logback and other logging frameworks and logback-access module integrates with Servlet containers, such as Tomcat and Jetty, to provide HTTP-access log functionality.
ELK
It is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.
