Elasticsearch is the future!
October 26, 2019
Elasticsearch is the future!
Score 9 out of 10
Vetted Review
Verified User
Overall Satisfaction with Elasticsearch
The most crucial piece of infrastructure behind my company's whole product line is Elasticsearch. Our company's big selling point is an extremely flexible data model for our customers who send us their data. We want them to be able to send us data in almost whatever shape or form they want (as long as it's valid JSON we'll take it) and yet, make it still searchable. And you know how we store that nearly-unrestricted free-form data? Elasticsearch!
- As I mentioned before, Elasticsearch's flexible data model is unparalleled. You can nest fields as deeply as you want, have as many fields as you want, but whatever you want in those fields (as long as it stays the same type), and all of it will be searchable and you don't need to even declare a schema beforehand!
- Elastic, the company behind Elasticsearch, is super strong financially and they have a great team of devs and product managers working on Elasticsearch. When I first started using ES 3 years ago, I was 90% impressed and knew it would be a good fit. 3 years later, I am 200% impressed and blown away by how far it has come and gotten even better. If there are features that are missing or you don't think it's fast enough right now, I bet it'll be suitable next year because the team behind it is so dang fast!
- Elasticsearch is really, really stable. It takes a lot to bring down a cluster. It's self-balancing algorithms, leader-election system, self-healing properties are state of the art. We've never seen network failures or hard-drive corruption or CPU bugs bring down an ES cluster.
- Elasticsearch paid support could be much better. Not only is it really expensive, but the reps just don't seem to be that knowledgeable and keep linking us to support documentation we've already found and read.
- I wouldn't call it missing functionality or a part that's hard to use perse, but upgrading from ES 5 to ES 6 is a PITA. Maaaan did they mess up a part of their data model so bad that when migrating, you have to restructure almost all your queries and transform almost all your data! I don't want to go into too many details here as some people may not be clued in on the concept of mapping types, but you can read more about it here https://www.elastic.co/guide/en/elasticsearch/reference/6.0/breaking-changes-6.0.html.
- This is no longer a problem in ES 6 but in versions 5 and before, reindexing is a PITA. You have to almost bring down the whole cluster to fix small problems such as missing fields or wrong types.
- I am not in finance and I suspect even if I was this would be hard to measure. But for sure, Elasticsearch has enabled us to have the most flexible data model in the industry for our customer's data, and in doing so we have attracted many many technical customers and got much of their $$$.
- One problem with Elasticsearch is that because it runs on the JVM, there can be some stop-the-world JVM garbage collections happening that can take down nodes and reduce indexing speed. The solution for that tends to be "let's just upgrade the CPU on that machine". And before you know it you are paying $$$ because this'll happen with 40+ machines.
- On the other hand, I do think that ES is more efficient than other systems and so it requires fewer nodes to keep it highly tolerant and available, so we probably saved some money that way.
Almost no one uses Solr anymore--most have migrated to Elasticsearch. I've never tried it myself but I heard Solr is much more difficult to configure and because it doesn't use a REST API, it locks you into Java and XML. XML--ick!
Lucene: Elasticsearch is built using Lucene instances for each index (the ES code essentially just glues together tons of Lucene instances), so it's not a fair comparison. But I suppose if you wanted the flexible data-model and you don't need the system to be distributed and highly available and parallel, Lucene would be a good choice.
Lucene: Elasticsearch is built using Lucene instances for each index (the ES code essentially just glues together tons of Lucene instances), so it's not a fair comparison. But I suppose if you wanted the flexible data-model and you don't need the system to be distributed and highly available and parallel, Lucene would be a good choice.
Do you think Elasticsearch delivers good value for the price?
Yes
Are you happy with Elasticsearch's feature set?
Yes
Did Elasticsearch live up to sales and marketing promises?
Yes
Did implementation of Elasticsearch go as expected?
Yes
Would you buy Elasticsearch again?
Yes