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Cloud backup services let users organize media and store a copy in case the original data is compromised. Google Photos has dominated the competition for media backup, AI search features, and editing for quite some time now.

However, the situation took a turn when the company announced that it would no longer offer unlimited storage space.

Several users searched for an alternative, and OneDrive is a name that emerged as one of the fierce competitors.

Microsoft OneDrive is a complete cloud storage solution that will let you create photo galleries and manage smart folders, and it has recently incorporated editing tools.

The Google Photos vs OneDrive debate is a tough one. The major question bothering many users is which platform is better and can be relied on as the ideal media backup companion.

This article aims to guide you through a few points and help you reach a better conclusion.

Google Photos and OneDrive offer cross-platform support. Microsofts product is available on multiple platforms, including Windows, iOS, Android, Web, and Mac, as you can access the same app everywhere.

Google Photos, on the other hand, only offers dedicated apps for iOS and Android. For Mac and Windows, youll have to rely on the web version.

The OneDrive gallery section is also integrated directly with the Photos app on Windows, while Google doesnt provide such integration features. Both also offer widgets across Android and iOS; thus, there isnt much to compete here.

Regarding the user interface, both platforms carry the material design theme guidelines. For efficient navigation, you get a handy bottom bar, and they also support the dark theme.

OneDrive offers built-in fingerprint protection, which Google Photos currently lacks. Although, the latter lets users lock pictures in separate folders inside the application.

OneDrive also provides a personal vault in the app, letting users store sensitive and important files. It is secured by a two-step verification and auto-locking feature and requires biometrics for successful access.

The AI-powered search feature of Google Photos is a definite edge for the platform, and OneDrives auto-tags feature doesnt match Googles powerful AI, which is a major differentiating factor.

Google Photos gets an edge in this category with its robust image editing features. It offers plenty of basic and a few advanced editing options. The auto-generated suggestions and filters are some of its standout attributes.

Microsoft OneDrive offers some editing features, but they are basic, including saturation, brightness, exposure, shadows, contrast, etc.

This concludes our article, and Google Photos is a clear winner due to its amazing editing and security features but yes it lacks in compatibility as compared to OneDrive.

If you want to read more informative content on Google Photos, click here.

PiunikaWeb started as purely an investigative tech journalism website with main focus on breaking or exclusive news. In no time, our stories got picked up by the likes of Forbes, Foxnews, Gizmodo, TechCrunch, Engadget, The Verge, Macrumors, and many others. Want to know more about us? Head here.

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Google Photos vs OneDrive: Which is the best cloud backup solution? - PiunikaWeb

Dell has devised a reference architecture-type design for a combined data lake/data warehouse using third-party partner software and its own server, storage, and networking hardware and software.

Like Databricks, Dremio, SingleStore, and Snowflake, Dell envisages a single data lakehouse construct. The concept is that you have a single, universal store with no need to run extract, transform and load (ETL) processes to get raw data selected and put into the proper form for use in a data warehouse. It is as if there is a virtual data warehouse inside the data lake.

Chhandomay Mandal, Dells director of ISG solution marketing, has written a blog about this, saying: Traditional data management systems, like data warehouses, have been used for decades to store structured data and make it available for analytics. However, data warehouses arent set up to handle the increasing variety of data Dell has devised a reference architecture-type design for a combined data lake/data warehouse using third-party partner software and its own server, storage and networking hardware and software text, images, video, Internet of things (IoT) nor can they support artificial intelligence (AI) and machine learning (ML) algorithms that require direct access to data.

Data lakes can, he says. Today, many organizations use a data lake in tandem with a data warehouse storing data in the lake and then copying it to the warehouse to make it more accessible but this adds to the complexity and cost of the analytics landscape.

What you need is one platform to do it all and Dells Validated Design for Analytics Data Lakehouse provides it, supporting business intelligence (BI), analytics, realtime data applications, data science, and machine learning. It is based on PowerEdge servers, PowerScale unified block and file arrays, ECS object storage, and PowerSwitch networking. The system can be housed on-premises or in a colocation facility.

The component software technologies include the Robin Cloud Native Platform, Apache Spark (open-source analytics engine), and Kafka (open-source distributed event streaming platform) with Delta Lake technologies. Databricks open-source Delta Lake software is built on top of Apache Spark and Dell is using Databricks Delta Lake in its own data lakehouse.

Dell is also partnering Rakuten-acquired Robin.IO with itsopensource Kubernetes platform.

Dell recently announced an external table access deal with Snowflake and says this data lakehouse validated design concept complements that. Presumably Snowflake external tables could reference the Dell data lakehouse.

With the above Dell graphic, things start to look complicated. A Dell Solution Brief contains more information, along with this table:

Clearly this is not an off-the-shelf system and needs a good deal of careful investigation and component selection and sizing before you cut a deal with Dell.

Interestingly, HPE has a somewhat similar product, Ezmeral Unified Analytics. This also uses Databricks Delta Lake technology, Apache Spark, and Kubernetes. HPE is running a Discover event this week, with many news expected. Perhaps the timing of Dells announcement is no accident.

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Dell builds its own partner-based data lakehouse Blocks and Files - Blocks and Files

Permiso, a start-up that focuses on cloud identity detection and response for cloud infrastructures, announced earlier this week that it has launched P0 Labs.

The P0 Labs name refers to the companys priority zero mission of detecting and responding to the latest cloud infrastructure attacks for its customers.

SC Media caught up with Paul Nguyen, the companys co-founder and co-CEO and Ian Ahl, vice president and head of P0 Labs, to talk about the companys unique identity-based approach to cloud security, and its plans to expand integrations and help customers adapt as nation-state actors start migrating to the cloud.

Let's begin by providing some background on the company and the story of how you started?

Nguyen: Permiso was started by Jason Martin and I three years ago when we were both executives at FireEye. We decided that cloud security was going to be the next frontier, very similar to the way we saw data centers evolve 20 years ago. We tried to buy a couple of cloud security companies and it gave us some insight into the market. FireEye wanted to look at detection and response as that next evolution for cloud security. Unfortunately, we werent able to execute on that strategy, so Jason and I left to do it on our own. We saw a huge opportunity for detection and response in the cloud security market which is still very much in its infancy. So were excited to do something thats completely white space, never been done before.

Is Permiso mainly a red team pen testing company? Or with your emphasis on detection and response are you taking the purple team approach?

Ahl: We are a cloud detection and response company and have some services built around that. I built the P0 Labs team with incident responders and pen testers for that purple team purpose of insinuating attacks on the red team side and having those responders watch whats going on. Our goal is to find bad guys. We take our knowledge to the front lines and bring it in there, but we also use the purple team approach to create the bad activity first so we can take that knowledge and codify it into our product. So a lot of times what well do is create malicious activity first, monitor what we are doing with the malicious activity, and then write detections associated with the malicious activity.

Whats different about the threat landscape in the cloud that requires a new approach from what the security industry has done in the past?

Ahl: The attackers want to move to the cloud for the same reason everyone else does: speed, scale, and impact. And thats the biggest differential from a capability standpoint. They know they can have a larger impact going to the cloud. Right now, we are at the phase where its mostly commodity attackers, ransomware and bitcoin mining, but now we are seeing advanced attackers starting to come into the cloud space. They have for years, but its just in larger numbers now. For example, APT29 is a group I worked on when I was at Mandiant. Those were the perpetrators of the SolarWinds incident. These are Russian nation-state threat actors, really top-tier when it comes to the groups that are tracked out there. And we know they are shifting now as well. They are getting into the vendor supply chain and are targeting cloud providers and targeting security vendors in the cloud so they can leverage that access to get into other environments.

So what are you doing to counteract this growing threat?

Nguyen: We are using identity as that main mechanism for us to detect evil. One of the main vectors were seeing is compromised credentials or exposed secrets: attackers gaining access via an initial set of credentials they compromise and can then follow that trail, and as they pivot they create other users and run other impact events.

The identity approach is very novel. Traditional approaches have been focused on networks, hosts, and IP addresses, which was a data center construct. In cloud, the cloud service providers are not exposing the network and hosts, they are providing services. The way you instrument those services is via APIs using credential. You hear about S3 buckets, which is data storage. And EC2, which is compute. How do you spin up more S3 or EC2? You have to have valid credentials to execute. Its not about a network or host. Its calling APIs using valid credential to spin up and spin down infrastructure, which is the power of the cloud.

Even if you look at traditional security products, its always about assets and hosts and networks: endpoint detection, network detection, email. In cloud, its completely different, its services. So how do you instrument services to build apps? People have a hard time when they switch to cloud in thinking about the security model in cloud. Our very first angel investor was Jason Chan, who used to be the vice president of information security at Netflix. Chan and his team at Netflix were on a very mature end of cloud and they gave us some of the initial constructs that we thought about in terms of what capabilities the mass security market would need as they start out with security in the cloud just getting in to cloud and finally getting where Netflix has evolved. We deconstructed what Jason Chan had done and said we can bring these capabilities down to where the customers are today.

How will P0 Labs make this happen?

Ahl:There are a lot of products, normal SIEMs that can take an event and let you know when something bad happens. What we do is group things around identity and credentials and pull all those events around attacker techniques and build rules around a session. A session is a grouping of events based on identity and credentials in a period of time. If I went into AWS and clicked create bucket and delete bucket and then attempted to spin up EC2 instances that would create hundreds of events to make that happen. A normal cloud SIEM would look event-by-event. We group that activity into one session. For example the system lets me know any time an identity attempts to escalate privileges within this type of resource. This allows us to describe complex logic because we group it all together.

Nguyen: Have you seen the Avengers movies? Theres the concept of the multiverse: parallel existences of same the person, but they are on different timelines. I may have 10 credentials in a cloud environment. So thats 10 different timelines and 10 different sessions I have to track independently of one another. Timeline 1 is malicious, timelines 2 and 3 are fine. When we see attackers, they are hopping across timelines and credentials. What we do is follow their trail and we havent seen anyone be able to do that multiverse tracking across sessions.

Permiso made news in January with its $10 million seed funding round. Given a looming recession, what's a realistic timeframe for future funding rounds and meeting your objectives for the future?

Nguyen: We arent thinking about fundraising right now, but we will be raising a round in the next 6-18 months based upon market demands. Were mainly focused on how to find evil in these new frontiers of cloud infrastructure. Today, theres not a lot of tooling to find the bad guys. I think we are a few months ahead of the market. We plan to extend our integrations. We formed a partnership with HashiCorp. to integrate with its vault. Were also looking to work with identity providers such as Okta, Ping, SailPoint, and Azure AD, thats a big part of our story. We also have customers requesting integrations into their CI/CD DevOps pipelines. Our heritage is former FireEye, former Mandiant. We know what evil looks like and Ian and his team know how to respond to evil. Ian has been responsible for tracking these threat actor groups. So our focus is staying ahead of the adversary. Get the best intel to understand where they are going, then build protections for our customers. An attacker can sit in an environment for a long time. We want to shorten that as much as possible.

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Permiso aims to help customers build a new identity-based security model for the cloud - SC Media