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IBM Storage Ceph vs. PrestoDB (or Presto)

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM Storage Ceph

    Score8 out of 10
    N/AIBM® Storage Ceph® is a software-defined storage platform that consolidates block, file and object storage to help organizations eliminate data silos and deliver a cloud-like experience while retaining the cost benefits and data sovereignty advantages of on-premises IT.N/A

    PrestoDB (or Presto)

    Score10 out of 10
    N/APresto is an open source SQL query engine designed to run queries on data stored in Hadoop or in traditional databases. Teradata supported development of Presto followed the acquisition of Hadapt and Revelytix.N/A
    Pricing
    IBM Storage CephPrestoDB (or Presto)
    Editions & Modules
    No answers on this topic
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    Offerings
    Pricing Offerings
    IBM Storage CephPrestoDB (or Presto)
    Free Trial
    NoNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
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    IBM Storage CephPrestoDB (or Presto)
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    User Ratings
    IBM Storage CephPrestoDB (or Presto)
    Likelihood to Recommend
    8.7
    (6 ratings)
    7.8
    (2 ratings)
    User Testimonials
    IBM Storage CephPrestoDB (or Presto)
    Likelihood to Recommend
    IBM
    Large scale data storage: Red Hat Ceph Storage is designed to be highly scalable and can handle large amounts of data. It's well suited for organizations that need to store and manage large amounts of data, such as backups, images, videos, and other types of multimedia content.Cloud-based deployments: Red Hat Ceph Storage can provide object storage services for cloud-based applications such as SaaS and PaaS offerings. It is well suited for organizations that are looking to build their own cloud storage infrastructure or to use it as a storage backend for their cloud-based applications.High-performance computing: Red Hat Ceph Storage can be used to provide storage for high-performance computing (HPC) applications, such as scientific simulations and other types of compute-intensive workloads. It's well suited for organizations that need to store
    Incentivized
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    Open Source
    Presto is for interactive simple queries, where Hive is for reliable processing. If you have a fact-dim join, presto is great..however for fact-fact joins presto is not the solution.. Presto is a great replacement for proprietary technology like Vertica
    Incentivized
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    Pros
    IBM
    • Highly resilient, almost every time we attempted to destroy the cluster it was able to recover from a failure. It struggled to when the nodes where down to about 30%(3 replicas on 10 nodes)
    • The cache tiering feature of Ceph is especially nice. We attached solid state disks and assigned them as the cache tier. Our sio benchmarks beat the our Netapp when we benchmarked it years ago (no traffic, clean disks) by a very wide margin.
    • Ceph effectively allows the admin to control the entire stack from top to bottom instead of being tied to any one storage vendor. The cluster can be decentralized and replicated across data centers if necessary although we didn't try that feature ourselves, it gave us some ideas for a disaster recovery solution. We really liked the idea that since we control the hardware and the software, we have infinite upgradability with off the shelf parts which is exactly what it was built for.
    Incentivized
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    Open Source
    • Linking, embedding links and adding images is easy enough.
    • Once you have become familiar with the interface, Presto becomes very quick & easy to use (but, you have to practice & repeat to know what you are doing - it is not as intuitive as one would hope).
    • Organizing & design is fairly simple with click & drag parameters.
    Incentivized
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    Cons
    IBM
    • GUI based mainetenence should be developed
    • Unable to detect storage latencies
    • VM to disk mapping should be visible so as to save some critical applications data in case of HDD failures
    Incentivized
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    Open Source
    • Presto was not designed for large fact fact joins. This is by design as presto does not leverage disk and used memory for processing which in turn makes it fast.. However, this is a tradeoff..in an ideal world, people would like to use one system for all their use cases, and presto should get exhaustive by solving this problem.
    • Resource allocation is not similar to YARN and presto has a priority queue based query resource allocation..so a query that takes long takes longer...this might be alleviated by giving some more control back to the user to define priority/override.
    • UDF Support is not available in presto. You will have to write your own functions..while this is good for performance, it comes at a huge overhead of building exclusively for presto and not being interoperable with other systems like Hive, SparkSQL etc.
    Incentivized
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    Alternatives Considered
    IBM
    MongoDB offers better search ability compared to Red Hat Ceph Storage but it’s more optimized for large number of object while Red Hat Ceph Storage is preferred if you need to store binary data or large individual objects. To get acceptable search functionality you really need to compile Red Hat Ceph Storage with another database where the search metadata related to Red Hat Ceph Storage objects are stored.
    Incentivized
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    Open Source
    Presto is good for a templated design appeal. You cannot be too creative via this interface - but, the layout and options make the finalized visual product appealing to customers. The other design products I use are for different purposes and not really comparable to Presto.
    Incentivized
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    Return on Investment
    IBM
    • Ceph allows my customer to scale out very fast.
    • Ceph allows distributing storage objects through multiple server rooms.
    • Ceph is fault-taulerant, meaning the customer can lose a server room and would still be able to access the storage.
    Incentivized
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    Open Source
    • Presto has helped scale Uber's interactive data needs. We have migrated a lot out of proprietary tech like Vertica.
    • Presto has helped build data driven applications on its stack than maintain a separate online/offline stack.
    • Presto has helped us build data exploration tools by leveraging it's power of interactive and is immensely valuable for data scientists.
    Incentivized
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    ScreenShots