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  1. Stackups
  2. DevOps
  3. Error Tracking
  4. Mobile Error Monitoring
  5. Crashlytics vs Kibana vs Vector

Crashlytics vs Kibana vs Vector

OverviewDecisionsComparisonAlternatives

Overview

Crashlytics
Crashlytics
Stacks1.0K
Followers614
Votes340
Kibana
Kibana
Stacks20.6K
Followers16.4K
Votes262
GitHub Stars20.8K
Forks8.5K
Vector
Vector
Stacks22
Followers53
Votes0
GitHub Stars3.6K
Forks250

Crashlytics vs Kibana vs Vector: What are the differences?

Introduction:

Crashlytics, Kibana, and Vector are all tools used for monitoring and analyzing data, but they have key differences that distinguish them from each other.

  1. Data Type Handling: Crashlytics is primarily focused on mobile app crash reporting, providing detailed insights into app crashes and their causes. Kibana, on the other hand, is a visualization tool that works in conjunction with Elasticsearch for analyzing and visualizing log data. Vector, as a high-performance data router, is used for efficiently handling and transmitting logs and metrics between various systems.

  2. User Interface: Crashlytics offers a user-friendly interface designed specifically for mobile app developers, making it easy to identify and prioritize issues. Kibana provides a more elaborate interface for creating custom dashboards and visualizations, catering to data analysts and engineers. Vector, being a data router, does not have a dedicated user interface but can be configured through its configuration files.

  3. Integration Capabilities: Crashlytics integrates seamlessly with mobile app development platforms like Firebase and Android Studio, making it easy for developers to incorporate crash reporting into their workflow. Kibana integrates with Elasticsearch as part of the Elastic Stack, enabling powerful search and analysis capabilities. Vector integrates with various data sources and destinations, serving as a versatile data pipeline tool.

  4. Scalability and Performance: Crashlytics is well-suited for handling crash data from mobile apps but may have limitations in scalability and performance when dealing with large volumes of data. Kibana, when paired with Elasticsearch, offers robust scalability and performance for analyzing massive datasets. Vector is designed for high performance and scalability, optimized for efficiently routing large amounts of data in real-time.

  5. Alerting and Monitoring: Crashlytics provides alerting features for notifying developers about critical app issues and trends, helping them address issues promptly. Kibana offers alerting and monitoring capabilities through its Watcher feature, enabling users to create custom alerts based on specified conditions. Vector supports integrations with monitoring tools like Prometheus and Grafana for real-time visibility into data flows and system health.

  6. Open Source vs. Proprietary: Vector is an open-source tool, providing transparency and flexibility for users to customize and contribute to its development. Crashlytics and Kibana are proprietary tools owned by Google and Elastic, respectively, offering enterprise support and maintenance but limiting the extent of customization and community-driven enhancements.

In Summary, Crashlytics specializes in mobile app crash reporting, Kibana excels in visualizing log data with Elasticsearch, and Vector serves as a high-performance data router for efficiently handling data flows.

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Advice on Crashlytics, Kibana, Vector

matteo1989it
matteo1989it

Jun 26, 2019

ReviewonKibanaKibanaGrafanaGrafanaElasticsearchElasticsearch

I use both Kibana and Grafana on my workplace: Kibana for logging and Grafana for monitoring. Since you already work with Elasticsearch, I think Kibana is the safest choice in terms of ease of use and variety of messages it can manage, while Grafana has still (in my opinion) a strong link to metrics

757k views757k
Comments
StackShare
StackShare

Jun 25, 2019

Needs advice

From a StackShare Community member: “We need better analytics & insights into our Elasticsearch cluster. Grafana, which ships with advanced support for Elasticsearch, looks great but isn’t officially supported/endorsed by Elastic. Kibana, on the other hand, is made and supported by Elastic. I’m wondering what people suggest in this situation."

663k views663k
Comments
abrahamfathman
abrahamfathman

Jun 26, 2019

ReviewonKibanaKibanaSplunkSplunkGrafanaGrafana

I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.

2.29M views2.29M
Comments

Detailed Comparison

Crashlytics
Crashlytics
Kibana
Kibana
Vector
Vector

Instead of just showing you the stack trace, Crashlytics performs deep analysis of each and every thread. We de-prioritize lines that don't matter while highlighting the interesting ones. This makes reading stack traces easier, faster, and far more useful! Crashlytics' intelligent grouping can take 50,000 crashes, distill them down to 20 unique issues, and then tell you which 3 are the most important to fix.

Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.

Vector provides a simple way for users to visualize and analyze system and application-level metrics in near real-time. It leverages the battle tested open source system monitoring framework, Performance Co-Pilot (PCP), layering on top a flexible and user-friendly UI. The UI polls metrics at up to 1 second resolution, rendering the data in completely configurable dashboards that simplify cross-metric correlation and analysis.

Instead of just showing you the stack trace, Crashlytics performs deep analysis of each and every thread. We de-prioritize lines that don't matter while highlighting the interesting ones. This makes reading stack traces easier, faster, and far more useful!;Crashlytics' intelligent grouping can take 50,000 crashes, distill them down to 20 unique issues, and then tell you which 3 are the most important to fix.;Now you'll get precise information on the performance of the devices that your apps run on. We'll let you know if the crash only happens on a specific model or generation of a device. We'll even tell you other information, like whether your app only crashes in landscape mode, or whether the proximity sensor is always on.;Through our smart reports, we'll provide key insights into your data so you can spend more time fixing and less time triaging.;Going one layer deeper, Crashlytics examines the operating system that your app is running on. We answer questions like: is it crashing only on jailbroken devices? Is this a memory issue? Does this only affect a specific version of iOS? Through our interactive reports, you'll know instantly.;Our cutting edge architecture can handle all the traffic you'll throw at us. For example, suppose a buggy update is released and all your users experience issues across all of their devices. Our system processes every crash in a record-breaking 18 milliseconds so you can take action — immediately.;Each crash we receive gets analyzed by our banks of servers. While pasting a stack trace is the simplest way to get it to you, we wanted to do better. We analyze the entire stack trace, for every crash, and apply carefully-tuned algorithms. Some lines are de-emphasized while others are highlighted, so we can take you straight to the threads and stack-frames that matter.;We've built a layer of intelligent post-processing to alert you to new issues in real-time. We've also built the channels to get that intelligence to you. Whether you're on the Crashlytics dashboard on your iPad, coding on your MacBook with Crashlytics for Mac, watching your third-party issue tracker or even your email inbox, you'll get notified when something important happens.;You're always in control — all notifications are customizable to minimize noise and maximize action.;The Crashlytics SDK uses a multi-step symbolication process to provide progressively higher levels of detail. We start with on-device symbolication. Once a crash report makes it into our system, stack frames are then re-processed against your application's dSYM on our servers. This two-step symbolication process, coupled with our advanced aggregation algorithms, provides the highest information fidelity available.;On average, Crashlytics adds only 40 KB — or the size of a single image — to the weight of your application.;We don't require linking against any additional frameworks or libraries.;When initialized at start-up, Crashlytics performs only the minimal amount of required work and defers the rest until a few seconds after app startup completes. This delay is configurable — we want your app to launch as quickly as possible;Our memory footprint has been carefully tuned to minimize overhead. We guarantee Crashlytics will not impact gameplay, video processing, or any memory-intensive operations you perform.;We care tremendously about the stability of your app and the experience for your users. If for any reason our SDK fails, its defensive design will ensure it has no negative impact.;We use run-time feature detection to ensure compatibility with iOS 4 to iOS 6 and beyond.
Flexible analytics and visualization platform;Real-time summary and charting of streaming data;Intuitive interface for a variety of users;Instant sharing and embedding of dashboards
-
Statistics
GitHub Stars
-
GitHub Stars
20.8K
GitHub Stars
3.6K
GitHub Forks
-
GitHub Forks
8.5K
GitHub Forks
250
Stacks
1.0K
Stacks
20.6K
Stacks
22
Followers
614
Followers
16.4K
Followers
53
Votes
340
Votes
262
Votes
0
Pros & Cons
Pros
  • 78
    Crash tracking
  • 56
    Mobile exception tracking
  • 53
    Free
  • 37
    Easy deployment
  • 25
    Ios
Pros
  • 88
    Easy to setup
  • 65
    Free
  • 45
    Can search text
  • 21
    Has pie chart
  • 13
    X-axis is not restricted to timestamp
Cons
  • 7
    Unintuituve
  • 4
    Works on top of elastic only
  • 4
    Elasticsearch is huge
  • 3
    Hardweight UI
No community feedback yet
Integrations
Jira
Jira
Pivotal Tracker
Pivotal Tracker
PagerDuty
PagerDuty
Asana
Asana
HipChat
HipChat
Campfire
Campfire
Trello
Trello
Bitbucket
Bitbucket
Hall
Hall
Logstash
Logstash
Elasticsearch
Elasticsearch
Beats
Beats
No integrations available

What are some alternatives to Crashlytics, Kibana, Vector?

New Relic

New Relic

The world’s best software and DevOps teams rely on New Relic to move faster, make better decisions and create best-in-class digital experiences. If you run software, you need to run New Relic. More than 50% of the Fortune 100 do too.

Datadog

Datadog

Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!

Grafana

Grafana

Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.

Instabug

Instabug

Instabug is a platform for Real-Time Contextual Insights that completely takes care of your bug reporting and user feedback process; to accelerate your workflow and allow you to release with confidence.

Prometheus

Prometheus

Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

Raygun

Raygun

Raygun gives you a window into how users are really experiencing your software applications. Detect, diagnose and resolve issues that are affecting end users with greater speed and accuracy.

Nagios

Nagios

Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.

AppSignal

AppSignal

AppSignal gives you and your team alerts and detailed metrics about your Ruby, Node.js or Elixir application. Sensible pricing, no aggressive sales & support by developers.

Netdata

Netdata

Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps

AppDynamics

AppDynamics

AppDynamics develops application performance management (APM) solutions that deliver problem resolution for highly distributed applications through transaction flow monitoring and deep diagnostics.

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