Interana comes out of stealth with event-driven analytics

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1 Interana comes out of stealth with event-driven analytics Analyst: Jason Stamper 21 Oct, 2014 Interana claims to offer data insight in seconds, rather than hours or days, with its new high-performance behavioral analytics offering. Founded by Facebook alumni and with an all-star cast of engineers, the company believes it can help analyze vast amounts of event stream data on commodity hardware. The 451 Take The signs are promising for Interana, despite it entering the incredibly competitive market that is high-performance analytics. Its founders certainly have the track record to inspire confidence, having been senior engineers at Facebook, and it has an experienced board to boot. Some companies will find it hard to contemplate a product that doesn't support their familiar SQL tools, but we see Interana's ease-of-use and 'full stack' approach as very exciting. Context Interana was founded in Ann Johnson, CEO, and Bobby Johnson, CTO, are a wife and husband who say they envisioned starting the company years ago. Ann formerly worked in process and integration engineering at Intel. Bobby was responsible for the infrastructure engineering team that scaled Facebook between , during which time, the company notes, Facebook grew from a few million college users to over a billion users globally. Bobby's team are said to have helped solve difficult scaling and infrastructure challenges and built technology such as Hive and Cassandra. Bobby personally wrote Scribe a server for aggregating log data streamed in real time from a large number of servers. Copyright The 451 Group 1

2 The third founder, Lior Abraham, created SCUBA, the most popular internal analytics tool at Facebook. It is used actively by more than half the company monthly, Interana says. Collectively, the founders say they wanted to bring some of what they had learned at Facebook to a broader audience, helping them solve scalability issues when attempting to analyze millions or billions of events. The company completed a series A funding round about 18 months ago, raising a total of $8.2m from Battery Ventures, Data Collective Venture Capital, SV Angel, Fuel Capital and YCombinator. Board members include Mark Leslie, former CEO, Veritas; Jeff Rothschild, vice president of engineering, Facebook; and Alex Benik, partner, Battery Ventures. Today, the company has just under 30 staff and is headquartered in Menlo Park, California, with another office in New York. Interana has been in private beta for six months. Technology Interana set out to build an analytics platform that allows users to analyze and explore key business metrics that matter such as growth, retention, conversion and engagement in seconds, rather than the hours or days it can often take with existing approaches such as more traditional relational databases. Interana consists of a data store (built from scratch, rather than being based on an open source database such as PostgreSQL), an analytic engine and front-end visualization interface. The data store is columnar, and automatically compresses data. Columns that are not referenced in a query don't get touched by that query, which saves wasting CPU cycles, cache or RAM. The firm says reads are pipelined at all levels, which is another way of saying that queries run lock-free: one query should not be held back by another query trying to access the same data. According to the firm, these design features, along with efficient use of SSD, memory and disk, gives the product blazing performance. It claims latency of just 10 nanoseconds per row, compared with 100-1,000 nanoseconds for some rival technology. Notably, the data store doesn't run entirely in memory like some other approaches such as VoltDB or SAP HANA Interana says the datasets of millions or billions of events it wants to store and analyze would simply be too large for that approach, and anyway it gets the performance it needs without it. Interana says it has benchmarked it at 100 million rows per core per second, allowing large and Copyright The 451 Group 2

3 complex queries to be done at run-time rather than via offline extract, transform and load (ETL) jobs. For data ingest, the company supports both streaming data in the continuous, synchronous import of data from sources like log files, Hadoop, data warehouses or via technologies like Kafka, Flume or Scribe; as well as a bulk importer for the asynchronous import of large amounts of data from a file store. It's also notable that the front-end visualization offers a coding-free environment users don't need to know SQL (in fact, Interana doesn't support it anyway). Instead, they explore and query the data using drop-down menus, graphs, charts and the like. Users can view or edit data, build custom queries, and visualize the results in multiple views. Behavior analytics features include sessions, funnels, cohorts, metrics and dashboards. Don't confuse Interana with a complex event processing (CEP) engine designed to kick off a business process when a certain event occurs or threshold is reached today, it's just for exploring and analyzing the data, although reports can be sent out via at regular intervals. It's partly the firm's focus on behavioral analytics that has enabled it to achieve the performance it claims: data is automatically arranged by time and by user, allowing single-pass queries with no intermediate sorts computation and network traffic is dramatically reduced as a result. It is also able to do full scans or intelligent sampling of raw data instead of pre-aggregations. To offer the full stack from data storage to visualization is no mean feat, and there's a concomitant need for several tiers of servers as a result: data servers, import servers, configuration database(s), and the analytics engine. Thankfully, Interana says it takes care of all of this complexity behind the scenes. As well as lacking support for SQL a deliberate move because the firm says it's too slow and prone to errors for analyzing such large datasets Interana doesn't support the R statistical programming language either. It's not really targeting that market anyway, aiming the product at business users who want fast, simple analytics, rather than data scientists. However, the company said it would be possible to add support for R if it gets enough demand from customers. Customers The company is targeting SaaS and Internet companies primarily, such as social media, Copyright The 451 Group 3

4 e-commerce, gaming, wearable devices and media and entertainment, but it could be applied in other areas such as analyzing call data records in telecoms firms. Beta customers include Sony, Jive, Asana, Tinder and Orange Silicon Valley. Competition Because it's geared for behavioral analysis, which usually involves some sort of time series, we'd have to compare Interana with time series databases such as GroveStreams or TempoIQ. OpenTSDB is an open source time-series database that sits on the open source HBase database and offers a simple user interface that can help get users started with basic line graph visualizations, but it doesn't claim to have real-time analytics, or to be able to handle the kind of scale and response time that Interana is talking about. It is possible to store time-series data in relational or NoSQL data stores, but the performance limitations with these approaches is what led Interana to develop an alternative approach in the first place. Relational databases capable of handling time-series data include Teradata's Aster Database, HP's Vertica and IBM's Informix. NoSQL databases that can handle time-series data include Apache Cassandra and Apache Accumulo. Depending on what customers are trying to do and how quickly they're trying to do it, Interana might find itself competing with more traditional data warehousing approaches, from the likes of Teradata, Oracle, HP Vertica, SAP HANA, Kognitio or Amazon Redshift (in the cloud). But remember that Interana doesn't support SQL queries, and instead is offering a full stack geared toward ease of use and speed. SWOT Analysis Strengths Weaknesses Very high performance of behavioral analysis of massive datasets, without the need for SQL programming or additional tools. Led by several engineers with excellent CVs, and helped along no doubt by an experienced board. Opportunities Threats We see strong demand for high-performance data analytics with better ease of use, as it's not just data scientists who want to better understand user behavior in the enterprise. Making analytics simpler to use, and not requiring SQL skills, could make the technology attractive to more employees in an organization than rival approaches. It's early yet because the company has only just come out of stealth mode, so all the challenges of being a small company that no one has heard of, in a very competitive market, apply. Interana deliberately doesn't support SQL, and can't yet be used to trigger business events, but only for data exploration. It's a competitive market, and there are open source mashups, data warehousing and in-memory database companies all vying for their piece of the action with different architectural approaches. Copyright The 451 Group 4

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