Software Alternatives & Startups

Looker VS StackGres

Compare Looker VS StackGres and see what are their differences

Looker

Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Rating
0 reviews
StackGres

Fully-featured platform for running PostgreSQL on Kubernetes

Rating
0 reviews
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Looker might be a bit more popular than StackGres. We know about 14 links to it since March 2021 and only 10 links to StackGres.

social mentions
14 vs 10
Data Dashboard popularity
100% vs 0%
alternatives listed
240+ vs 29

Base details

Website, pricing, platforms and company facts side by side.

Looker
StackGres
Website looker.com stackgres.io
Pricing
Company Startup from the United States —
Listed in

About Looker and StackGres

In their own words, as submitted to SaaSHub.

Looker
StackGres

Looker is a business intelligence platform with an analytics-oriented application server that sits on top of relational data stores. The Looker platform includes an end-user interface for exploring data, a reusable development paradigm for creating data discovery experiences, and an extensible...

Read more about Looker

No description of StackGres yet.

Features and specs

What each product offers, as listed by its team.

Looker 6 features
StackGres 5 features
  • Powerful Data Modeling
    Looker uses LookML, a proprietary modeling language, making it possible to transform raw data into meaningful metrics and dimensions, providing deep insights without needing SQL expertise.
  • Ease of Use
    Its intuitive user interface enables non-technical users to create visualizations and reports with relative ease, reducing the workload on data teams.
  • Customization
    Looker offers extensive customization options for data exploration and visualization, allowing dashboards and reports to be tailored to specific user needs.
  • Embedded Analytics
    Provides robust capabilities for embedding analytics into applications or portals, broadening the scope of data-driven decision-making throughout the organization.
  • Real-time Data
    Supports real-time data analytics by querying live data, which ensures up-to-date insights and helps in making timely decisions.
  • Integrations
    Looker integrates seamlessly with a wide range of databases and cloud data warehouses, including Google BigQuery, Amazon Redshift, and Snowflake.

Possible disadvantages

  • Learning Curve
    LookML, while powerful, can be complex for beginners who are not already familiar with data modeling or SQL, resulting in a steep learning curve.
  • Cost
    Looker can be expensive, especially for small businesses, as pricing is typically based on the number of users and the data volume processed.
  • Performance
    Query performance can sometimes be slow, especially with complex data models and large data sets, which may impact the user experience.
  • Customization Constraints
    While Looker offers great customization, certain advanced customizations may require significant expertise and time, posing a potential barrier.
  • Limited Offline Capabilities
    Looker is primarily designed for online use, so it lacks robust offline capabilities, which can be a limitation for users who need access to data in situations without internet connectivity.
  • Integrated PostgreSQL Management
    StackGres provides a comprehensive suite for managing PostgreSQL clusters, simplifying configuration, deployment, and maintenance.
  • Scalability
    StackGres supports dynamic scaling of PostgreSQL clusters, allowing for flexible resource allocation based on workload demands.
  • Kubernetes Native
    Built on Kubernetes, StackGres leverages its powerful orchestration capabilities for high availability and container management.
  • Security Features
    Includes advanced security features like SSL/TLS, authentication, and role-based access control to safeguard data and connections.
  • Monitoring and Alerting
    Comes with integrated monitoring and alerting tools, providing insights into database performance and health metrics.

Possible disadvantages

  • Complexity
    The Kubernetes-based environment can introduce complexity for users unfamiliar with container orchestration and management.
  • Resource Intensive
    Running StackGres requires significant computational resources, which might be overkill for small-scale or less demanding applications.
  • Learning Curve
    New users may face a steep learning curve in mastering StackGres for effective management of PostgreSQL in a Kubernetes environment.
  • Cost Considerations
    While powerful, using Kubernetes and associated resources for StackGres can lead to higher operational costs.
  • Dependency on Kubernetes
    Requires a functional Kubernetes cluster, which might be a barrier for organizations not currently using Kubernetes.

Analysis

An editorial look at what each product does well and who it suits.

Looker
StackGres

Overall verdict

  • Looker is generally considered a robust solution for organizations looking to enhance their data-driven decision-making capabilities. Its flexibility, extensibility, and ease of use make it a strong contender in the BI space, though it may require some learning and setup effort to fully utilize its features.

Why this product is good

  • Looker is a data analytics platform that provides powerful tools for data exploration, visualization, and business intelligence. It offers a user-friendly interface and is known for its ability to connect to a wide variety of data sources. Looker's LookML, a modeling language, allows users to define data relationships and calculations, making it easier to create custom reports and dashboards. Additionally, it integrates well with other tools and supports collaboration with data teams.

Recommended for

  • Companies seeking scalable and flexible business intelligence solutions.
  • Organizations that need to integrate multiple data sources.
  • Teams looking for a collaborative platform with custom reporting capabilities.
  • Users who prefer a code-based approach to data modeling and analysis.

No analysis of StackGres yet.

Videos

Walkthroughs and reviews on video.

Looker 3 videos + Add
StackGres 0 videos + Add

Looker Review

More videos

  • - How To Use Looker as a Business User
  • - Looker Review - Off The Shelf Reviews

No StackGres videos yet. You could help us improve this page by suggesting one.

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Looker
StackGres
100% 100%
0% 0%
0% 0%
100% 100%
100% 100%
0% 0%
0% 0%
100% 100%

User comments

Share your experience with using Looker and StackGres. For example, how are they different and which one is better?

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

Looker no reviews yet
StackGres no reviews yet

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We have no reviews of StackGres yet. Be the first one to post

Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Looker 14 mentions
StackGres 10 mentions
  • edit home page to add folder section
    Then in the "foldername" you can have 5 folders, each one for each of the groups. This means that when group1 enters looker.com, his default page will be the "foldername", which contains group1folder (he cannot see the rest of the... Source: over 3 years ago
  • Stars, tables, and activities: How do we model the real world?
    Even if you want to make Wide Tables, combining fact and dimensions is often the easiest way to create them, so why not make them available? Looker, for example, is well suited to dimensional models because it takes care of the joins... - Source: dev.to / almost 4 years ago
  • dbt for Data Quality Testing & Alerting at FINN
    We take daily snapshots of test results, aggregate them, and send Looker dashboards to the appropriate teams. - Source: dev.to / over 4 years ago

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  • TimescaleDB compresses time-series data
    At StackGres [1] we find Timescale to be one of the most used extensions. Timescale is quite a successful project! StackGres is actually the first solution recommended by Timescale for self-hosting with Kubernetes operators [2]. So if... - Source: Hacker News / 4 months ago
  • Show HN: SQL-tap – Real-time SQL traffic viewer for PostgreSQL and MySQL
    * Latency. Yes, yes, yes, they add "microseconds" vs "milliseconds for queries", and that's true, but just part of the story. There's an extra hop. There's two extra sets of TCP layers being traversed. If the hop is local (say a sidecar,... - Source: Hacker News / 8 months ago
  • Application Less Containers
    This is conceptually similar to what we did for Postgres extensions at the StackGres [1] project. I gave a talk at a Kubecon about it [2]. However, this scheme is not perfect. Some Kubernetes security solutions enforce immutable... - Source: Hacker News / about 1 year ago

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Alternatives to Looker and StackGres

When comparing Looker and StackGres, you can also consider the following products.