What is Periscope and what are its top alternatives?
Top Alternatives to Periscope
- Looker
We've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way. ...
- Mode
Created by analysts, for analysts, Mode is a SQL-based analytics tool that connects directly to your database. Mode is designed to alleviate the bottlenecks in today's analytical workflow and drive collaboration around data projects. ...
- Chartio
Chartio is a cloud-based business analytics solution on a mission to enable everyone within an organization to access, explore, transform and visualize their data. ...
- Tableau
Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click. ...
- Zoom
Zoom unifies cloud video conferencing, simple online meetings, and cross platform group chat into one easy-to-use platform. Our solution offers the best video, audio, and screen-sharing experience across Zoom Rooms, Windows, Mac, iOS, Android, and H.323/SIP room systems. ...
- Google Analytics
Google Analytics lets you measure your advertising ROI as well as track your Flash, video, and social networking sites and applications. ...
- Google Tag Manager
Tag Manager gives you the ability to add and update your own tags for conversion tracking, site analytics, remarketing, and more. There are nearly endless ways to track user behavior across your sites and apps, and the intuitive design lets you change tags whenever you want. ...
- Mixpanel
Mixpanel helps companies build better products through data. With our powerful, self-serve product analytics solution, teams can easily analyze how and why people engage, convert, and retain to improve their user experience. ...
Periscope alternatives & related posts
- Real time in app customer chat support4
- GitHub integration4
- Reduces the barrier of entry to utilizing data1
- Price3
related Looker posts
Our primary source of monitoring and alerting is Datadog. We’ve got prebuilt dashboards for every scenario and integration with PagerDuty to manage routing any alerts. We’ve definitely scaled past the point where managing dashboards is easy, but we haven’t had time to invest in using features like Anomaly Detection. We’ve started using Honeycomb for some targeted debugging of complex production issues and we are liking what we’ve seen. We capture any unhandled exceptions with Rollbar and, if we realize one will keep happening, we quickly convert the metrics to point back to Datadog, to keep Rollbar as clean as possible.
We use Segment to consolidate all of our trackers, the most important of which goes to Amplitude to analyze user patterns. However, if we need a more consolidated view, we push all of our data to our own data warehouse running PostgreSQL; this is available for analytics and dashboard creation through Looker.
We are a consumer mobile app IOS/Android startup. The app is instrumented with branch and Firebase. We use Google BigQuery. We are looking at tools that can support engagement and cohort analysis at an early stage price which we can grow with. Data Studio is the default but it would seem Looker provides more power. We don't have much insight into Amplitude other than the fact it is a popular PM tool. Please provide some insight.
- Empowering for SQL-first analysts4
- Easy report building3
- Collaborative query building3
- In-app customer chat support2
- Awesome online and chat support2
- Integrated IDE with SQL + Python for analysis2
- Auto SQL query to Python dataframe1
related Mode posts
- Great UI2
- Affordable for a BI solution2
- Join multiple databases2
related Chartio posts
- Capable of visualising billions of rows6
- Intuitive and easy to learn1
- Responsive1
- Very expensive for small companies3
related Tableau posts
Looking for the best analytics software for a medium-large-sized firm. We currently use a Microsoft SQL Server database that is analyzed in Tableau desktop/published to Tableau online for users to access dashboards. Is it worth the cost savings/time to switch over to using SSRS or Power BI? Does anyone have experience migrating from Tableau to SSRS /or Power BI? Our other option is to consider using Tableau on-premises instead of online. Using custom SQL with over 3 million rows really decreases performances and results in processing times that greatly exceed our typical experience. Thanks.
Hello everyone,
My team and I are currently in the process of selecting a Business Intelligence (BI) tool for our actively developing company, which has over 500 employees. We are considering open-source options.
We are keen to connect with a Head of Analytics or BI Analytics professional who has extensive experience working with any of these systems and is willing to share their insights. Ideally, we would like to speak with someone from companies that have transitioned from proprietary BI tools (such as PowerBI, Qlik, or Tableau) to open-source BI tools, or vice versa.
If you have any contacts or recommendations for individuals we could reach out to regarding this matter, we would greatly appreciate it. Additionally, if you are personally willing to share your experiences, please feel free to reach out to me directly. Thank you!
- Web conferencing made easy25
- Remote control option16
- Draw on screen13
- Very reliable12
- In-meeting chat is pretty good11
- Free9
- Pair programming sessions with shared controls9
- Easy to share meeting links/invites8
- Good Sound Quality7
- Cloud recordings for meetings6
- Great mobile app5
- Virtual backgrounds4
- Recording Feature4
- Other people use it4
- User Friendly actions4
- Reactions (emoticons)2
- Auto reconnecting2
- Chrome extension is great to easily create meetings2
- While sharing screen, you can still see your video2
- Mute all participants at once2
- When ending the videocall, everybody gets kicked2
- Different options for blocking chat2
- Easily share video with audio1
- /zoom on Slack1
- Registration form1
- Meant for business and education1
- Zoom0
- Limited time if you are a basic member20
- Limited Storage14
- Hate how sharing your screen defaults to Full Screen11
- Quality isn't great (Free)10
- No cursor highlight on screenshare.9
- Potential security flaws8
- Onboarding process for new users is not intuitive7
- Virtual background quality isn't good5
- Security5
- Editing can be improved4
- Doesn't handle switching audio sources well4
- The native calendar is buggy4
- Dashboard can be improved4
- Pornographic material displayed3
- Any body can get in it3
- Not many emojis3
- Past chat history is not saved3
- Recording Feature3
- En In reality,the chat in the meet not is excelent,noo3
- Zoom lags a lot3
related Zoom posts
Using Screenhero via Slack was getting to be pretty horrible. Video and sound quality was often times pretty bad and worst of all the service just wasn't reliable. We all had high hopes when the acquisition went through but ultimately, the product just didn't live up to expectations. We ended up trying Zoom after I had heard about it from some friends at other companies. We noticed the video/sound quality was better, and more importantly it was super reliable. The Slack integration was awesome (just type /zoom and it starts a call)
You can schedule recurring calls which is helpful. There's a G Suite (Google Calendar) integration which lets you add a Zoom call (w/dial in info + link to web/mobile) with the click of a button.
Meeting recordings (video and audio) are really nice, you get recordings stored in the cloud on the higher tier plans. One of our engineers, Jerome, actually built a cool little Slack integration using the Slack API and Zoom API so that every time a recording is processed, a link gets posted to the "event-recordings" channel. The iOS app is great too!
#WebAndVideoConferencing #videochat
Server side
We decided to use Python for our backend because it is one of the industry standard languages for data analysis and machine learning. It also has a lot of support due to its large user base.
Web Server: We chose Flask because we want to keep our machine learning / data analysis and the web server in the same language. Flask is easy to use and we all have experience with it. Postman will be used for creating and testing APIs due to its convenience.
Machine Learning: We decided to go with PyTorch for machine learning since it is one of the most popular libraries. It is also known to have an easier learning curve than other popular libraries such as Tensorflow. This is important because our team lacks ML experience and learning the tool as fast as possible would increase productivity.
Data Analysis: Some common Python libraries will be used to analyze our data. These include NumPy, Pandas , and matplotlib. These tools combined will help us learn the properties and characteristics of our data. Jupyter notebook will be used to help organize the data analysis process, and improve the code readability.
Client side
UI: We decided to use React for the UI because it helps organize the data and variables of the application into components, making it very convenient to maintain our dashboard. Since React is one of the most popular front end frameworks right now, there will be a lot of support for it as well as a lot of potential new hires that are familiar with the framework. CSS 3 and HTML5 will be used for the basic styling and structure of the web app, as they are the most widely used front end languages.
State Management: We decided to use Redux to manage the state of the application since it works naturally to React. Our team also already has experience working with Redux which gave it a slight edge over the other state management libraries.
Data Visualization: We decided to use the React-based library Victory to visualize the data. They have very user friendly documentation on their official website which we find easy to learn from.
Cache
- Caching: We decided between Redis and memcached because they are two of the most popular open-source cache engines. We ultimately decided to use Redis to improve our web app performance mainly due to the extra functionalities it provides such as fine-tuning cache contents and durability.
Database
- Database: We decided to use a NoSQL database over a relational database because of its flexibility from not having a predefined schema. The user behavior analytics has to be flexible since the data we plan to store may change frequently. We decided on MongoDB because it is lightweight and we can easily host the database with MongoDB Atlas . Everyone on our team also has experience working with MongoDB.
Infrastructure
- Deployment: We decided to use Heroku over AWS, Azure, Google Cloud because it is free. Although there are advantages to the other cloud services, Heroku makes the most sense to our team because our primary goal is to build an MVP.
Other Tools
Communication Slack will be used as the primary source of communication. It provides all the features needed for basic discussions. In terms of more interactive meetings, Zoom will be used for its video calls and screen sharing capabilities.
Source Control The project will be stored on GitHub and all code changes will be done though pull requests. This will help us keep the codebase clean and make it easy to revert changes when we need to.
- Free1.5K
- Easy setup927
- Data visualization891
- Real-time stats698
- Comprehensive feature set406
- Goals tracking182
- Powerful funnel conversion reporting155
- Customizable reports139
- Custom events try83
- Elastic api53
- Updated regulary15
- Interactive Documentation8
- Google play4
- Walkman music video playlist3
- Industry Standard3
- Advanced ecommerce3
- Irina2
- Easy to integrate2
- Financial Management Challenges -2015h2
- Medium / Channel data split2
- Lifesaver2
- Confusing UX/UI11
- Super complex8
- Very hard to build out funnels6
- Poor web performance metrics4
- Very easy to confuse the user of the analytics3
- Time spent on page isn't accurate out of the box2
related Google Analytics posts
This is my stack in Application & Data
JavaScript PHP HTML5 jQuery Redis Amazon EC2 Ubuntu Sass Vue.js Firebase Laravel Lumen Amazon RDS GraphQL MariaDB
My Utilities Tools
Google Analytics Postman Elasticsearch
My Devops Tools
Git GitHub GitLab npm Visual Studio Code Kibana Sentry BrowserStack
My Business Tools
Slack
Functionally, Amplitude and Mixpanel are incredibly similar. They both offer almost all the same functionality around tracking and visualizing user actions for analytics. You can track A/B test results in both. We ended up going with Amplitude at BaseDash because it has a more generous free tier for our uses (10 million actions per month, versus Mixpanel's 1000 monthly tracked users).
Segment isn't meant to compete with these tools, but instead acts as an API to send actions to them, and other analytics tools. If you're just sending event data to one of these tools, you probably don't need Segment. If you're using other analytics tools like Google Analytics and FullStory, Segment makes it easy to send events to all your tools at once.
Google Tag Manager
related Google Tag Manager posts
Hi,
This is a question for best practice regarding Segment and Google Tag Manager. I would love to use Segment and GTM together when we need to implement a lot of additional tools, such as Amplitude, Appsfyler, or any other engagement tool since we can send event data without additional SDK implementation, etc.
So, my question is, if you use Segment and Google Tag Manager, how did you define what you will push through Segment and what will you push through Google Tag Manager? For example, when implementing a Facebook Pixel or any other 3rd party marketing tag?
From my point of view, implementing marketing pixels should stay in GTM because of the tag/trigger control.
If you are using Segment and GTM together, I would love to learn more about your best practice.
Thanks!
Mixpanel
- Great visualization ui144
- Easy integration108
- Great funnel funcionality78
- Free58
- A wide range of tools22
- Powerful Graph Search15
- Responsive Customer Support11
- Nice reporting2
- Messaging (notification, email) features are weak2
- Paid plans can get expensive2
- Limited dashboard capabilities1
related Mixpanel posts
Functionally, Amplitude and Mixpanel are incredibly similar. They both offer almost all the same functionality around tracking and visualizing user actions for analytics. You can track A/B test results in both. We ended up going with Amplitude at BaseDash because it has a more generous free tier for our uses (10 million actions per month, versus Mixpanel's 1000 monthly tracked users).
Segment isn't meant to compete with these tools, but instead acts as an API to send actions to them, and other analytics tools. If you're just sending event data to one of these tools, you probably don't need Segment. If you're using other analytics tools like Google Analytics and FullStory, Segment makes it easy to send events to all your tools at once.
Hi there, we are a seed-stage startup in the personal development space. I am looking at building the marketing stack tool to have an accurate view of the user experience from acquisition through to adoption and retention for our upcoming React Native Mobile app. We qualify for the startup program of Segment and Mixpanel, which seems like a good option to get rolling and scale for free to learn how our current 60K free members will interact in the new subscription-based platform. I was considering AppsFlyer for attribution, and I am now looking at an affordable yet scalable Mobile Marketing tool vs. building in-house. Braze looks great, so does Leanplum, but the price points are 30K to start, which we can't do. I looked at OneSignal, but it doesn't have user flow visualization. I am now looking into Urban Airship and Iterable. Any advice would be much appreciated!