Elastic Search vs Equalum comparison

Elastic and Google are both solutions in the Cloud Data Integration category. Elastic is ranked #9 with an average rating of 8.3, while Google is ranked #30. Elastic holds a 2.0% mindshare in CDI, compared to Google’s 0.8% mindshare. Additionally, 97% of Elastic users are willing to recommend the solution, compared to 100% of Google users who would recommend it.

Elastic Search

Read 75 Elastic Search reviews

7,566 Views
605 Comparison Views

97% willing to recommend

Equalum

Read 7 Equalum reviews

599 Views
150 Comparison Views

100% willing to recommend

Elastic Search

Equalum

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Executive SummaryUpdated on Dec 3, 2024

Elastic Search and Equalum compete in the data integration and management sector. Elastic Search seems to have an advantage in scalability and data visualization, while Equalum stands out in ease of use and efficient data integration.

Features: Elastic Search provides strong log monitoring capabilities with its integration of Logstash and Kibana, enabling effective data visualization and scalability. It also offers features like X-Pack for enhanced security and supports comprehensive data retrieval. Equalum shines with its no-code data integration workflows, effective streaming ETL capabilities, and integration of technologies such as Kafka and Spark, making it a robust platform for data integration and migration.

Room for Improvement: Elastic Search could improve its machine learning functionalities and alerting features for better large-scale deployments. Users face challenges with data ingestion. Equalum needs enhanced documentation and better integration with databases like Oracle and SQL Server, along with improvements in replication speed and security features.

Ease of Deployment and Customer Service: Elastic Search supports on-premises and hybrid cloud deployments with strong community support, although official technical service can be slow. Equalum emphasizes ease of deployment with its intuitive interface, supporting both on-premises and cloud models, and offers positively rated technical support.

Pricing and ROI: Elastic Search has a free version but incurs higher costs with premium features like security and alerting in its tiered licenses. ROI is sometimes seen as moderate due to technical skill and licensing costs. Equalum features straightforward, component-based pricing perceived as costlier than some competitors but offers significant savings in development time due to its integration efficiencies.

To learn more, read our detailed Elastic Search vs. Equalum Report (Updated: September 2025).

Buyer's Guide

Elastic Search vs. Equalum

September 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Elastic Search

Ranking in Cloud Data Integration

9th

Average Rating

8.2

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Indexing and Search (1st), Search as a Service (1st), Vector Databases (3rd)

Equalum

Ranking in Cloud Data Integration

30th

Average Rating

9.2

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

Data Integration (66th), Data Replication (19th)

Mindshare comparison

As of October 2025, in the Cloud Data Integration category, the mindshare of Elastic Search is 2.0%, up from 1.0% compared to the previous year. The mindshare of Equalum is 0.8%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Integration Market Share Distribution
Product	Market Share (%)
Elastic Search	2.0%
Equalum	0.8%
Other	97.2%

Cloud Data Integration

Featured Reviews

Louis McCoy

Director, Software Engineering at Optum Technology

Searches through billions of documents have become impressively fast and consistent

The seamless scalability is something I see as among the best features Elastic Search offers. The speed with which Elastic Search is able to search through all of the documents we place into it is quite remarkable, as we search through 65 billion documents in less than a second in most cases, on a constant consistent basis. I find configuring relevant searches within Elastic Search platform very straightforward. Elastic Search is easily scalable. The customer support for Elastic Search is quite good. I advise others looking into using Elastic Search to think about the future of your platform and where you intend it to be in five years, and based on that, which version of Elastic Search best suits the needs of your platform. Additionally, jump into the AI products first as you're in the planning phase so that as you're filling out your data, the AI products and machine learning products can enrich the data real-time early on in the process, which will save you a lot of time later. The overall performance of the platform, scalability of the platform and other additional features, especially when it comes to AI, really earn the nine.

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Joel Buck

Director of Enterprise Architecture at a pharma/biotech company with 10,001+ employees

There is no better product for CDC and streaming on Kafka

The Equalum user interface is extremely easy to use. I would rank it really highly on user-friendliness. The only issue with the user interface is it doesn't supply everything that you need for somebody who has to work with Equalum. For example, when you get deep into development, there are many areas where you have to go to the command line to do things and the Equalum user interface does not have that functionality. The deployment of their flows needs improvement. It doesn't work with a typical Git branching and CI/CD deployment strategy. If you have multiple projects, all working in one Equalum environment, separating out their work is something that you have to design into your implementation, as opposed to baked into the product.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The solution has good security features. I have been happy with the dashboards and interface."

"Dashboard is very customizable."

"The UI is very nice, and performance wise it's quite good too."

"The tool's stability and performance are good."

"The speed with which Elastic Search is able to search through all of the documents we place into it is quite remarkable, as we search through 65 billion documents in less than a second in most cases, on a constant consistent basis."

"The stability of Elasticsearch was very high, and I would rate it a ten."

"It helps us to analyse the logs based on the location, user, and other log parameters."

"I like how it allows us to connect to Kafka and get this data in a document format very easily. Elasticsearch is very fast when you do text-based searches of documents. That area is very good, and the search is very good."

More Elastic Search pros

"The main impact for Oracle LogMiner is the performance. Performance is drastically reduced if you use the solution’s Oracle Binary Log Parser. So, if we have 60 million records, initially it used to take a minute. Now, it takes a second to do synchronization from the source and target tables."

"It's a really powerful platform in terms of the combination of technologies they've developed and integrated together, out-of-the-box. The combination of Kafka and Spark is, we believe, quite unique, combined with CDC capabilities. And then, of course, there are the performance aspects. As an overall package, it's a very powerful data integration, migration, and replication tool."

"It's got it all, from end-to-end. It's the glue. There are a lot of other products out there, good products, but there's always a little bit of something missing from the other products. Equalum did its research well and understood the requirements of large enterprise and governments in terms of one tool to rule them all, from a data migration integration perspective."

"All our architectural use cases are on a single platform, not multiple platforms. You don't have to dump into different modules because it is the same module everywhere."

"Equalum is real-time. If you are moving from an overnight process to a real-time process, there is always a difference in what reports and analytics show compared to what our operational system shows. Some of our organizations, especially finance, don't want those differences to be shown. Therefore, going to a real-time environment makes the data in one place match the data in another place. Data accuracy is almost instantaneous with this tool."

"Equalum provides a single platform for core architectural use cases, including CDC replication, streaming ETL, and batch ETL. That is important to our clients because there is no other single-focus product that covers these areas in that much detail, and with this many features on the platform. The fact that they are single-minded and focused on CDC and ETL makes this such a rich solution. Other solutions cover these things a little bit in their multi-function products, but they don't go as deep."

"I found two features in Equalum that I consider the most valuable. One is that Equalum is a no-code tool. You can do your activities on its graphical interface, which doesn't require complex knowledge of extracting, changing, or loading data. Another feature of Equalum that I like the most is that it monitors the data transfers and tells you if there's any issue so that you can quickly check and correct it. Equalum also tells you where the problem lies, for example, if it's a hardware or communication issue."

"Equalum has resulted in system performance improvements in our organization. Now, I am ingressing data off of multiple S3 sources, doing data processing, and formatting a schema. This would usually take me a couple of days, but now it takes me hours."

Cons

"The metadata gets stored along with indexes and isn't queryable."

"Kibana should be more friendly, especially when building dashboards."

"The solution's integration and configuration are not easy. Not many people know exactly what to do."

"We'd like to see more integration in the future, especially around service desks or other ITSM tools."

"The one area that can use improvement is the automapping of fields."

"Elastic Enterprise Search can improve by adding some kind of search that can be used out of the box without too much struggle with configuration. With every kind of search engine, there is some kind of special function that you need to do. A simple out-of-the-box search would be useful."

"New Relic could be more flexible, similar to Elasticsearch."

"Something that could be improved is better integrations with Cortex and QRadar, for example."

More Elastic Search cons

"I should be able to see only my project versus somebody else's garbage. That is something that would be good in future. Right now, the security is by tenants, but I would like to have it by project, e.g., this project has this source and flows in these streams, and I have access to this on this site."

"There is not enough proven integration with other vendors. That is what needs to be worked on. Equalum hasn't tested anything between vendors, which worries our clients. We need more proven vendor integration. It is an expensive product and it needs to support a multi-vendor approach."

"Right now, they have a good notification system, but it is in bulk. For example, if I have five projects running and I put a notification, the notification comes back to me for all five projects. I would like the notification to come back only for one project."

"Their UI could use some work. Also, they could make it just a little faster to get around their user interface. It could be a bit more intuitive with things like keyboard shortcuts."

"The deployment of their flows needs improvement. It doesn't work with a typical Git branching and CI/CD deployment strategy."

"If you need to use the basic features of Equalum, for example, you don't even need data integration, then many competitors in the market can give you basic features. For instance, if you need batch ETL, you can pick among solutions in the market that have been around longer than Equalum. What needs improvement in Equalum is replication, as it could be faster. Equalum also needs better integration with specific databases such as Oracle and Microsoft SQL Server."

"They need to expand their capabilities in some of the targets, as well as source connectors, and native connectors for a number of large data sources and databases. That's a huge challenge for every company in this area, not just Equalum."

Pricing and Cost Advice

"The solution is less expensive than Stackdriver and Grafana."

"It can be expensive."

"This product is open-source and can be used free of charge."

"An X-Pack license is more affordable than Splunk."

"We are using the open-sourced version."

"The tool is an open-source product."

"The solution is affordable."

"The version of Elastic Enterprise Search I am using is open source which is free. The pricing model should improve for the enterprise version because it is very expensive."

More Elastic Search pricing and cost advice

"Equalum is rather expensive compared to its competitors. So, you have to make up that cost in time savings, and we usually do that. If we are saving money, it is because we are reducing our development time."

"Equalum was reasonably priced. It is not like those million dollar tools, such as Informatica."

"They have a very simple approach to licensing. They don't get tied up with different types of connectivity to different databases. If you need more connectors or if you need more CPU, you just add on. It's component-based pricing."

"Equalum licensing costs vary, but I won't be able to give information on its fees."

"As soon as you have more than six users, Equalum is lower in cost [than Talend] and if the group gets bigger, it's quite a big delta. If more users want to use it, you don't end up with an increase in licensing costs, so that makes it very easy. And if you need more licenses or more sources, it's a very simple upgrade methodology."

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Top Industries

By visitors reading reviews

Computer Software Company

14%

Financial Services Firm

13%

Manufacturing Company

Government

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	32
Midsize Enterprise	9
Large Enterprise	36

By reviewers
Company Size	Count
Small Business	2
Midsize Enterprise	1
Large Enterprise	4

Questions from the Community

What do you like most about ELK Elasticsearch?

Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time anal...

See all answers

What is your experience regarding pricing and costs for ELK Elasticsearch?

We used the open-source version of Elasticsearch, which was free.

See all answers

What needs improvement with ELK Elasticsearch?

We could benefit from refining the machine learning models that we currently use in Elastic Search, along with the possibility to integrate agents, intelligent artificial intelligence, form of agen...

See all answers

Why should I use Equalum instead of LogMiner?

You'd want to use the Equalium Oracle Binary Log Parser because it's just better than the LogMiner. Sure, LogMiner is made by Oracle and probably the team knows some insight to make it efficient th...

See all answers

Is Equalum compatible with all databases?

I'm using Equalum's data replication software for Oracle because that's the one database it's designed for. While it may sound limiting, when you find out how many solutions it can provide for you ...

See all answers

Can I use Equalum for free?

No, it's not free but you can benefit from a free trial, though. There's an option to try their platform for a limited amount of time, so that may be useful to help you decide if you want to contin...

See all answers

Comparisons

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Algolia vs Elastic Search

Compared 8% of the time

Milvus vs Elastic Search

Compared 7% of the time

Azure AI Search vs Elastic Search

Compared 6% of the time

Faiss vs Elastic Search

Compared 5% of the time

More Elastic Search Competitors

No data available

Product Reports

Buyer's Guide

Elastic Search

October 2025

Download Elastic Search product report

Buyer's Guide

Equalum

October 2025

Download Equalum product report

Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud

No data available

Overview

Elasticsearch is a prominent open-source search and analytics engine known for its scalability, reliability, and straightforward management. It's a favored choice among enterprises for real-time data search, analysis, and visualization. Open-source Elasticsearch is free, offering a comprehensive feature set and scalability. It allows full control over deployments but requires managing and maintaining the infrastructure. On the other hand, Elastic Cloud provides a managed service with features like automated provisioning, high availability, security, and global reach.

Elasticsearch excels in handling time-sensitive data and complex search requirements across large datasets. Its scalability allows it to handle growing data volumes efficiently, maintaining high performance and fast response times. Integrated with Kibana, Elasticsearch enables powerful data visualization, providing real-time insights crucial for data-driven decision-making.

Elastic Cloud reduces operational overhead and improves scalability and performance, though it comes with associated costs. It is available on your preferred cloud provider — AWS, Azure, or Google Cloud. Customers who want to manage the software themselves, whether on public, private, or hybrid cloud, can download the Elastic Stack.

At its core, Elasticsearch is renowned for its full-text search capabilities, capable of performing complex queries and supporting features like fuzzy matching and auto-complete.

Peer reviews from various professionals highlight its strengths and weaknesses. Pros include its detection and correlation features, flexibility, cloud-readiness, extensibility, and efficient search capabilities. However, users have noted challenges like steep learning curves, data analysis limitations, and integration complexities. The platform is generally viewed as stable and scalable, with varying degrees of satisfaction regarding its usability and feature set.

In summary, Elasticsearch stands out for its high-speed search, scalability, and versatile analytics, making it a go-to solution for organizations managing large datasets. Its adaptability to different enterprise needs, robust community support, and continuous development keep it at the forefront of enterprise search and analytics solutions. However, potential users should be aware of its learning curve and the need for skilled personnel for optimization.

Elastic

Equalum is a fully-managed, end-to-end data integration and real-time data streaming platform, powered by industry-leading change data capture (CDC) tech and modern data transformation capabilities (streaming ETL and ELT). Equalum's enterprise-grade platform features intuitive UI allowing you to build robust, real-time data pipelines in minutes.

Google

Sample Customers

T-Mobile, Adobe, Booking.com, BMW, Telegraph Media Group, Cisco, Karbon, Deezer, NORBr, Labelbox, Fingerprint, Relativity, NHS Hospital, Met Office, Proximus, Go1, Mentat, Bluestone Analytics, Humanz, Hutch, Auchan, Sitecore, Linklaters, Socren, Infotrack, Pfizer, Engadget, Airbus, Grab, Vimeo, Ticketmaster, Asana, Twilio, Blizzard, Comcast, RWE and many others.

SIEMENS, GSK, Wal-Mart, T Systems

Buyer's Guide

Elastic Search vs. Equalum

September 2025

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