What users are saying about
37 Ratings
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106 Ratings
37 Ratings
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Score 8.4 out of 101

Elasticsearch

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106 Ratings
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Score 8.7 out of 101

Likelihood to Recommend

Apache Kafka

Apache Kafka is extremely well suited in near real-time scenarios, high volume or multi-location projects. It can solve escalation problems for a fraction of the cost other solutions do and it has the flexibility of open source scenarios.
Juan Francisco Tavira profile photo

Elasticsearch

ElasticSearch is hands down, the absolute best solution for logging in a virtualization environment. The Kibana front end to ElasticSearch is extremely intuitive, even computer novices can be trained on how to chain together tags in the Apache Lucene syntax to extract the data they need. Once the deploy process is nailed down and system is engineered, the logging structure can remain fairly static until the next major revision. Compared to Splunk, with an administrator well versed in the ElasticSearch suite, will save an organization upwards of 10's of thousands of dollars a year even with the caveats mentioned earlier.As a developer looking for a quick and simple search engine which has little configuration required, ElasticSearch is fast and perfect for that solution. Literally throw JSON records in to the database and push a request to get JSON out, exceptionally straightforward.
Colby Shores profile photo

Pros

Apache Kafka

  • High volume/performance throughput environments
  • Low latency projects
  • Multiple consumers for the same data, reprocessing, long-lasting information
Juan Francisco Tavira profile photo

Elasticsearch

  • Effortless to set up. Literally set the memory thresholds for Java and start throwing JSON formatted records in to the database, it "Just Works". Even clustering is automated as the cluster finds other ElasticSearch servers on the network and assigns each a name.
  • Very simple to use interface either through it's RESTFUL API (ala Curl) or via its speedy protocol on port 9300. Once records are added, the very easy to use Apache Lucene syntax is supported to extract data.
  • It's search capabilities are fast on huge datasets, even on very modest hardware. Our organization operates in the hundreds of servers taking thousands of requests a second, each with it's own log w/ a 2 week retention. The ElasticSearch server we recently decommissioned was Pentium 4 Netburst class Xeon, it rarely skipped a beat.
Colby Shores profile photo

Cons

Apache Kafka

  • Still a bit inmature, some clients have required recoding in the last few versions
  • New feaures coming very fast, several upgrades a year may be required
  • Not many commercial companies provide support
Juan Francisco Tavira profile photo

Elasticsearch

  • Elasticsearch can struggle if you're trying to create too many new indexes at the same time.
No photo available

Likelihood to Renew

Apache Kafka

Apache Kafka 9.0
Based on 1 answer
Kafka is quickly becoming core product of the organization, indeed it is replacing older messaging systems. No better alternatives found yet
Juan Francisco Tavira profile photo

Elasticsearch

Elasticsearch 10.0
Based on 1 answer
We're pretty heavily invested in ElasticSearch at this point, and there aren't any obvious negatives that would make us reconsider this decision.
Aaron Gussman profile photo

Usability

Apache Kafka

No score
No answers yet
No answers on this topic

Elasticsearch

Elasticsearch 10.0
Based on 1 answer
To get started with Elasticsearch, you don't have to get very involved in configuring what really is an incredibly complex system under the hood. You simply install the package, run the service, and you're immediately able to begin using it. You don't need to learn any sort of query language to add data to Elasticsearch or perform some basic searching.If you're used to any sort of RESTful API, getting started with Elasticsearch is a breeze. If you've never interacted with a RESTful API directly, the journey may be a little more bumpy. Overall, though, it's incredibly simple to use for what it's doing under the covers.
No photo available

Implementation

Apache Kafka

No score
No answers yet
No answers on this topic

Elasticsearch

Elasticsearch 9.0
Based on 1 answer
Do not mix data and master roles. Dedicate at least 3 nodes just for Master
No photo available

Alternatives Considered

Apache Kafka

Kafka is faster and more scalable, also "free" as opensource (albeit we deploy using a commercial distribution). Infrastructure tends to be cheaper. On the other hand, projects must adapt to Kafka APIs that sometimes change and BAU increases until a major 1.x version comes out and adds stability to the product.
Juan Francisco Tavira profile photo

Elasticsearch

Other services, such as Alienvault or MongoDB, are not designed to integrate as well with parsing log data. Graphite was much more difficult to work into an usable product as it does not integrate as easily with log parsing plugins. Elasticsearch had the right features to provide what we needed out of the box rather than requiring us to write numerous custom tools just to get the basic features.
No photo available

Return on Investment

Apache Kafka

  • Easier deployment and horizontal scalability
  • Messaging cost reduction
  • Developments require adaptation and some paradigm shift to interoperate with Kafka
Juan Francisco Tavira profile photo

Elasticsearch

  • ElasticSearch was able to meet the high demands of our product when it mattered most.
  • Implementation of ElasticSearch was easy and quick, saving on the cost of implementation.
  • Managing ElasticSearch is very easy. With the right monitoring tools in place, it really is "set it and forget it".
No photo available

Pricing Details

Apache Kafka

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

Elasticsearch

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

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