Nov
06
2019
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Neo4j introduces new cloud service to simplify building a graph database

Neo4j, a popular graph database, is available as an open-source product for anyone to download and use. Its enterprise product aimed at larger organizations is growing fast, but the company recognized there was a big market in between those two extremes, and today it introduced a new managed cloud service called Aura.

They wanted something in the product family for smaller companies, says Emil Eifrem, CEO and co-founder at Neo4j . Aura really gives these smaller players a much more manageable offering with flexible pricing options. “To get started with an enterprise project can run hundreds of thousands of dollars per year. Whereas with Aura, you can get started for about 50 bucks a month, and that means that it opens it up to new segments of the market,” Eifrem told TechCrunch. As he points out, even a startup on a shoestring budget can afford $50 a month.

Aura operates on a flexible pricing model, and offers the kind of value proposition you would expect from a cloud version of the product. The company deals with all of the management, security and updates for you. It will also scale as needed to meet your data requirements as you grow. The idea is to allow developers to concentrate on simply building applications and let Neo4j deal with the database for you.

He says over time, he could see larger businesses, which don’t want to deal with the management side of developing a graph database application, also using the cloud product. “Why would you want to operate your own database? You should probably focus on your core business and building applications to support that core business,” he said. But he recognizes change happens slowly in larger organizations, and not every business will be comfortable with a managed service. That’s why they are offering different options to meet different requirements.

Graph databases allow you to see connections between data. It is the underlying technology, for example, in a social networking app, that lets you see the connection between people you know and people your friends know. It is also the technology on an e-commerce site that can offer recommendations based on what you bought before because people who buy a certain product are more likely to purchase other related products.

Apr
09
2019
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Google Cloud challenges AWS with new open-source integrations

Google today announced that it has partnered with a number of top open-source data management and analytics companies to integrate their products into its Google Cloud Platform and offer them as managed services operated by its partners. The partners here are Confluent, DataStax, Elastic, InfluxData, MongoDB, Neo4j and Redis Labs.

The idea here, Google says, is to provide users with a seamless user experience and the ability to easily leverage these open-source technologies in Google’s cloud. But there is a lot more at play here, even though Google never quite says so. That’s because Google’s move here is clearly meant to contrast its approach to open-source ecosystems with Amazon’s. It’s no secret that Amazon’s AWS cloud computing platform has a reputation for taking some of the best open-source projects and then forking those and packaging them up under its own brand, often without giving back to the original project. There are some signs that this is changing, but a number of companies have recently taken action and changed their open-source licenses to explicitly prevent this from happening.

That’s where things get interesting, because those companies include Confluent, Elastic, MongoDB, Neo4j and Redis Labs — and those are all partnering with Google on this new project, though it’s worth noting that InfluxData is not taking this new licensing approach and that while DataStax uses lots of open-source technologies, its focus is very much on its enterprise edition.

“As you are aware, there has been a lot of debate in the industry about the best way of delivering these open-source technologies as services in the cloud,” Manvinder Singh, the head of infrastructure partnerships at Google Cloud, said in a press briefing. “Given Google’s DNA and the belief that we have in the open-source model, which is demonstrated by projects like Kubernetes, TensorFlow, Go and so forth, we believe the right way to solve this it to work closely together with companies that have invested their resources in developing these open-source technologies.”

So while AWS takes these projects and then makes them its own, Google has decided to partner with these companies. While Google and its partners declined to comment on the financial arrangements behind these deals, chances are we’re talking about some degree of profit-sharing here.

“Each of the major cloud players is trying to differentiate what it brings to the table for customers, and while we have a strong partnership with Microsoft and Amazon, it’s nice to see that Google has chosen to deepen its partnership with Atlas instead of launching an imitation service,” Sahir Azam, the senior VP of Cloud Products at MongoDB told me. “MongoDB and GCP have been working closely together for years, dating back to the development of Atlas on GCP in early 2017. Over the past two years running Atlas on GCP, our joint teams have developed a strong working relationship and support model for supporting our customers’ mission critical applications.”

As for the actual functionality, the core principle here is that Google will deeply integrate these services into its Cloud Console; for example, similar to what Microsoft did with Databricks on Azure. These will be managed services and Google Cloud will handle the invoicing and the billings will count toward a user’s Google Cloud spending commitments. Support will also run through Google, so users can use a single service to manage and log tickets across all of these services.

Redis Labs CEO and co-founder Ofer Bengal echoed this. “Through this partnership, Redis Labs and Google Cloud are bringing these innovations to enterprise customers, while giving them the choice of where to run their workloads in the cloud, he said. “Customers now have the flexibility to develop applications with Redis Enterprise using the fully integrated managed services on GCP. This will include the ability to manage Redis Enterprise from the GCP console, provisioning, billing, support, and other deep integrations with GCP.”

Nov
01
2018
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Neo4j nabs $80M Series E as graph database tech flourishes

Neo4j has helped popularize the graph database. Today it was rewarded with an $80 million Series E to bring their products to a wider market in what could be the company’s last private fundraise.

The round was led by One Peak Partners and Morgan Stanley Expansion Capital with participation from existing investors Creandum, Eight Roads and Greenbridge Partners. Today’s investment exactly doubles their previous amount bringing the total raised to $160 million.

Neo4j founder and CEO Emil Eifrem didn’t want to discuss valuation, calling it essentially a vanity metric. “We’re not sharing that. I never understood that. It’s just weird bragging rights. It makes no sense to customers, and makes no sense to anyone,” he said referring to the valuation.

Graph view of Neo4j funding rounds. Graphic: Neo4j

When you bring a company like Morgan Stanley on as an investor, it could be interpreted as a kind of signal that the company is thinking ahead to going public. While Eifrem wasn’t ready to commit to anything, he suggested that this is very likely the last time he raises funds privately. He says that he doesn’t like to think in terms of how he will exit so much as building a good company and seeing where that takes him. “If your mental framework is around building a great company, you’re going to have all kinds of options along the way. So that’s what I’m completely focused on,” Eifrem explained.

In 2016, when his company got a $36 million Series D investment, Eifrem says that they were working to expand in the enterprise. They have been successful with around 200 enterprise customers to their credit including Walmart, UBS, IBM and NASA. He says their customers include 20 of the top 25 banks and 7 of the top 10 retailers.

This year, the company began expanding into artificial intelligence. It makes sense. Graph databases help companies understand the connections in large datasets and AI usually involves large amounts of data to drive the learning models.

Two common graph database use case examples are the social graph on a social site like Facebook, which lets you see the connections between you and your friends or the purchase graph on an Ecommerce site like Amazon which lets you see if you bought one product, chances are you’ll also be interested in these others (based on your purchase history and what other consumers have done who have bought similar products).

Eifrem wants to use the money to expand the company internationally and provide localized service in terms of language and culture wherever their customers happen to be. As an example, he says today European customers might get an English speaking customer service agent if they called in for help. He wants to provide service and the website in the local language and the money should help accomplish that.

Neo4j was founded in 2007 as an open source project. Companies and individuals can still download the base product for free, but the company has also built a successful and growing commercial business on top of that open source project. With an $80 million runway, the next stop could be Wall Street.

Sep
20
2018
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AI could help push Neo4j graph database growth

Graph databases have always been useful to help find connections across a vast data set, and it turns out that capability is quite handy in artificial intelligence and machine learning too. Today, Neo4j, the makers of the open source and commercial graph database platform, announced the release of Neo4j 3.5, which has a number of new features aimed specifically at AI and machine learning.

Neo4j founder and CEO Emil Eifrem says he had recognized the connection between AI and machine learning and graph databases for a while, but he says that it has taken some time for the market to catch up to the idea.

“There has been a lot momentum around AI and graphs…Graphs are very fundamental to AI. At the same time we were seeing some early use cases, but not really broad adoption, and that’s what we’re seeing right now,” he explained.

AI graph uses cases. Graphic: Neo4j

To help advance AI uses cases, today’s release includes a new full text search capability, which Eifrem says has been one of the most requested features. This is important because when you are making connections between entities, you have to be able to find all of the examples regardless of how it’s worded — for example, human versus humans versus people.

Part of that was building their own indexing engine to increase indexing speed, which becomes essential with ever more data to process. “Another really important piece of functionality is that we have improved our data ingestion very significantly. We have 5x end-to-end performance improvements when it comes to importing data. And this is really important for connected feature extraction, where obviously, you need a lot of data to be able to train the machine learning,” he said. That also means faster sorting of data too.

Other features in the new release include improvements to the company’s own Cypher database query language and better visualization of the graphs to give more visibility, which is useful for visualizing how machine learning algorithms work, which is known as AI explainability. They also announced support for the Go language and increased security.

Graph databases are growing increasingly important as we look to find connections between data. The most common use case is the knowledge graph, which is what lets us see connections in a huge data sets. Common examples include who we are connected to on a social network like Facebook, or if we bought one item, we might like similar items on an ecommerce site.

Other use cases include connected feature extraction, a common machine learning training techniques that can look at a lot of data and extract the connections, the context and the relationships for a particular piece of data, such as suspects in a criminal case and the people connected to them.

Neo4j has over 300 large enterprise customers including Adobe, Microsoft, Walmart, UBS and NASA. The company launched in 2007 and has raised $80 million. The last round was $36 million in November 2016.

Oct
24
2017
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New Neo4J platform gives developers a set of tools for building enterprise graph applications

 Neo4j builds tools for creating graph databases, and today at its GraphConnect conference in New York City, it announced a new platform for developers to build graph-based applications using a common set of services.
Emil Eifrem, Neo4j co-founder, says while the concept of graph databases has steadily gained popularity in recent years, the databases need to connect to various enterprise systems. Read More

Jan
15
2015
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Neo Technology Bags $20M As Graph Databases Get Hot

Graph Databases book from O'Reilly. Neo Technology, developers of the neo4j graph database have been growing steadily, and investors have noticed, rewarding them with a $20M Series C pay day. Creandum led the round joined by Dawn Capital and current investors Fidelity Growth Partners Europe, Sunstone Capital and Conor Venture Partners. The company’s last funding round was in November, 2012 for $11M, and this latest… Read More

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