What users are saying about

Apache Kafka

24 Ratings

Elasticsearch

87 Ratings

Apache Kafka

24 Ratings
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Score 8.6 out of 101

Elasticsearch

87 Ratings
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Score 8.9 out of 101

Add comparison

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 the gold standard for text-based search. Across large data sets it performs admirably, and we will certainly make it our first choice search solution in the future. For a use case where needs are simple and regular database queries might suffice, Elasticsearch may or may not provide any benefits.
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Pros

  • High volume/performance throughput environments
  • Low latency projects
  • Multiple consumers for the same data, reprocessing, long-lasting information
Juan Francisco Tavira profile photo
  • Indexing. Elasticsearch can index thousands of documents per second.
  • Searching. Elasticsearch provides plenty of options for querying your data to get just the right information back.
  • Scalability. Elasticsearch has built-in features for replicating data and distributing load, so you don't have to invest a ton of time and effort into third-party or customized clustering and/or sharding solutions.
  • Backup. Elasticsearch has built-in options for backing up your data. If you're dealing with a large cluster, backing things up can get rather interesting from a storage perspective, but Elasticsearch has worked very well for us thus far.
  • Recovery. If part of your cluster goes offline, Elasticsearch generally does a decent job of staying online and recovering from the outage. Occasionally you'll lose nodes that house all copies of a given set of shards (which isn't fun), but Elasticsearch still handles that situation as well as can be expected.
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Cons

  • 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
  • The online documentation is very difficult to use, both as a teaching tool and as a quick reference. The search syntax is arcane and not particularly "human friendly" and examples from the documentation are often insufficiently detailed to apply directly.
  • ElasticSearch is touted as "schemaless" when in fact mappings (aka schemas) are required for all but the most basic use cases.
Aaron Gussman profile photo

Likelihood to Renew

Apache Kafka9.0
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
Elasticsearch10.0
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

No score
No answers yet
No answers on this topic
Elasticsearch10.0
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.
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Implementation

No score
No answers yet
No answers on this topic
Elasticsearch9.0
Based on 1 answer
Do not mix data and master roles. Dedicate at least 3 nodes just for Master
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Alternatives Considered

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
Power and simplicity along with performance.
Josh Kramer profile photo

Return on Investment

  • 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 has allowed us to shave off many (> 100 is some cases) milliseconds from our API response times.
  • Elasticsearch coupled with Kibana has allowed us a whole new level of visibility into our log data.
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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