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Google BigTable vs InfluxDB comparison

 

Comparison Buyer's Guide

Executive Summary

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

Google BigTable
Ranking in Non-Relational Databases
12th
Average Rating
8.6
Number of Reviews
2
Ranking in other categories
No ranking in other categories
InfluxDB
Ranking in Non-Relational Databases
3rd
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
9
Ranking in other categories
Open Source Databases (12th), Network Monitoring Software (53rd), IT Infrastructure Monitoring (46th), NoSQL Databases (5th)
 

Mindshare comparison

As of April 2025, in the Non-Relational Databases category, the mindshare of Google BigTable is 4.4%, up from 1.9% compared to the previous year. The mindshare of InfluxDB is 6.5%. It is calculated based on PeerSpot user engagement data.
Non-Relational Databases
 

Featured Reviews

ES
Extremely scalable, quite stable and easy to deploy
We're just a user of the product. We don't have a relationship with Google. We're currently using the latest version. We just request it on the Google environment when we need to use it. At this point, after a year of using the solution, I'd rate it eight out of ten. We still have a lot to learn about it, so it's difficult to really give it full marks or to say we aren't happy with it. Right now, because of where our company is in terms of size and needs, I would say it's better for us to have Bitware.
PedroCampos - PeerSpot reviewer
A powerful, lightweight time series database with a simple query language and easy setup
Influx has TICK Stack, which contains multiple services and multiple products that work together. InfluxDB is just a time series database, and it works really well. I haven't yet had the time to look into the new stack based on Influx 2.0, but currently, as a time series database, InfluxDB is working the way it is supposed to work. In terms of features that I would like to see or have, in the community version, some features are not available. I would like to have clustering and authentication in the community version. I would also like to have high availability features, such as replication, active-active, etc. If they can put an extra plugin or service on top of it, it would be something interesting. I am not sure if they have high availability to make it data center-aware for clustering. For example, I am not sure whether you can have it at different locations with big clusters that are location-aware. Even in their documentation or presentation, they talk too little about high availability and extended clusters with different locations. They might already have it in the newer versions. We have Influx 1.8 in our production in the stage and internal workloads environments. The other products in their ecosystem, such as Chronograf, can be improved. Chronograf is a dashboarding or visualization layer product, and that, for sure, can be improved.

Quotes from Members

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

Pros

"This solution is much more scalable than more traditional databases - at least the ones we are aware of."
"I like the drive and the support of this program."
"The solution is very powerful."
"The most valuable features of InfluxDB are the documentation and performance, and the good plugins metrics in the ecosystem."
"In our case, it started with a necessity to fill the gap that we had in monitoring. We had very reactive monitoring without trend analysis and without some advanced features. We were able to implement them by using a time series database. We are able to have all the data from applications, logs, and systems, and we can use a simple query language to correlate all the data and make things happen, especially with monitoring. We could more proactively monitor our systems and our players' trends."
"The most valuable feature of the solution is we can use InfluxDB to integrate with and plug into any other tools."
"The user interface is well-designed and easy to use. It provides a clear overview of the data, making it simple to understand the information at hand."
"The most valuable features are aggregating the data and integration with Graphana for monitoring."
"The platform operates very quickly. It is easy to configure, connect, and query and integrates seamlessly with Grafana."
"InfluxDB's best feature is that it's a cloud offering. Other good features include its time-series DB, fast time-bulk queries, and window operations."
 

Cons

"The pricing of the solution needs to be improved."
"The solution doesn't have much of a user interface."
"InfluxDB can improve by including new metrics on other technologies. They had some changes recently to pool data from endpoints but the functionality is not good enough in the industry."
"In terms of features that I would like to see or have, in the community version, some features are not available. I would like to have clustering and authentication in the community version."
"InfluxDB is generally stable, but we've encountered issues with the configuration file in our ticket stack. For instance, a mistake in one of the metrics out of a hundred KPIs can disrupt data collection for all KPIs. This happens because the agent stops working if there's an issue with any configuration part. To address this, it is essential to ensure that all configurations are part of the agent's EXE file when provided. This makes it easier to package the agent for server installation and ensures all KPIs are available from the server. Additionally, the agent cannot encrypt and decrypt passwords for authentication, which can be problematic when monitoring URLs or requiring authentication tokens. This requires additional scripting and can prolong service restart times."
"The solution's UI can be more user-friendly."
"I've tried both on-premises and cloud-based deployments, and each has its limitations."
"The error logging capability can be improved because the logs are not very informative."
"InfluxDB cannot be used for high-cardinality data. It's also difficult and time-consuming to write queries, and there are some issues with bulk API."
 

Pricing and Cost Advice

"I would like to see better pricing. It is not too expensive, but it isn't cheap either."
"The tool is an open-source product."
"We are using the open-source version of InfluxDB."
"InfluxDB is open-source, but there are additional costs for scaling."
"InfluxDB recently increased its price. It is very expensive now."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
15%
Computer Software Company
12%
Manufacturing Company
10%
Educational Organization
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

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What do you like most about InfluxDB?
InfluxDB is a database where you can insert data. However, it would be best if you had different components for alerting, data sending, and visualization. You need to install tools to collect data ...
What needs improvement with InfluxDB?
InfluxDB is generally stable, but we've encountered issues with the configuration file in our ticket stack. For instance, a mistake in one of the metrics out of a hundred KPIs can disrupt data coll...
What is your primary use case for InfluxDB?
I use the solution to store and manage data from various sensors in a production environment. I have developed a system where data from these sensors is communicated through an OPC UA receiver and ...
 

Comparisons

No data available
 

Also Known As

BigTable
No data available
 

Overview

 

Sample Customers

Absolutdata, Aerospike, Affini-Tech, Akselos, Alacris Theranostics, Allthecooks, AloTech, APMEX Inc., Applibot, Appogee, BeDataDriven, Bitmovin, CloudBerry
ebay, AXA, Mozilla, DiDi, LeTV, Siminars, Cognito, ProcessOut, Recommend, CATS, Smarsh, Row 44, Clustree, Bleemeo
Find out what your peers are saying about Google BigTable vs. InfluxDB and other solutions. Updated: March 2025.
845,406 professionals have used our research since 2012.