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ClickHouse vs. Titan Distributed Graph Database

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    ClickHouse

    Score7.2 out of 10
    N/AClickHouse is an open-source, column-oriented OLAP database system enabling real-time analytical reports using SQL queries. With linear scalability, it handles trillions of rows and petabytes of data. ClickHouse Cloud offers a scalable serverless solution for real-time analytics.N/A

    Titan

    Score8 out of 10
    N/ATitan is an open-source distributed graph database developed by Aurelius. Aurelius is now part of Datastax (since February 2015).N/A
    Pricing
    ClickHouseTitan
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    ClickHouseTitan
    Free Trial
    YesNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    YesNo
    Entry-level Setup FeeOptionalNo setup fee
    Additional DetailsPay for what is used: It automatically scales up and down compute resources based on the user's workload It scales storage and compute separately It automatically scales unused resources down to zero so that users don’t pay for idle services—
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    Best Alternatives
    ClickHouseTitan
    Small Businesses
    No answers on this topic
    Neo4j
    Score9 out of 10
    Medium-sized Companies
    Snowflake
    Score8.7 out of 10
    Neo4j
    Score9 out of 10
    Enterprises
    Snowflake
    Score8.7 out of 10
    Neo4j
    Score9 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    ClickHouseTitan
    Likelihood to Recommend
    10.0
    (2 ratings)
    8.0
    (1 ratings)
    User Testimonials
    ClickHouseTitan
    Likelihood to Recommend
    ClickHouse, Inc.
    The most important thing when using ClickHouse is to be clear that the scenarios in which you want to use it really are the right ones. Many users think that when a database is very fast for a specific use case, it can be extrapolated to other contexts (most of the time different) in which a previous analysis has not been carried out.
    ClickHouse is an analytical database, as such, it should be used for such purposes, where the information is stored correctly, the data volumes are really large and the queries to be performed are not the typical traditional queries on several columns with multiple aggregations. ClickHouse is not the solution for this.
    On the other hand, if your case is not one of the above, it is quite possible that ClickHouse can help you. Where ClickHouse shines is when you are looking for aggregation over a particular column in large volumes of data.
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    Open Source
    Titan is definitely a good choice, but it has its learning curve. The documentation may lack in places, and you might have to muster answers from different sources and technologies. But at its core, it does the job of storing and querying graph databases really well. Remember that titan itself is not the whole component, but utilizes other technologies like cassandra, gremlin, tinkerpop, etc to do many other things, and each of them has a learning curve. I would recommend titan for a team, but not for a single person. For single developer, go with Neo4j.
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    Pros
    ClickHouse, Inc.
    • Their MergeTree table engine provide impressive performance for data insert in bulk
    • Not only data insert but also the way MergeTree engine uses Primary Keys to sort the data and perform data skipping based on the granules its also their secret for ridiculous fast queries
    • Data compression its also great
    • They provide especial table engines that allow you to read data directly from other sources like S3
    • Since its written with C++ you have very granular data types and especial ones like enum, LowCardinality and etc, they save you a lot of storage since are stored as integer values
    • ClickHouse functions besides the ones that respect ANSI Standards are also awesome and useful
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    Open Source
    • Titan is really good for abstraction of underlying infrastructure. You can choose between different storage engine of your choice.
    • Open source, backed by community, and free.
    • Supports tinkerpop stack which is backed by apache.
    • Uses gremlin for query language making the whole query structure standardized and open for extension if another graph database comes along in future.
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    Cons
    ClickHouse, Inc.
    • Avro data manipulation
    • Kafka consistency
    • DDL operations errors (by replica configuration)
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    Open Source
    • The community is lacking deep documentation. I had to spend many nights trying to figure many things on my own. As graph databases will grow popular, I am sure this will be improved.
    • Not enough community support. Even in SO you might not find many questions. Though there are some users in SO who quickly answer graph database questions. Need more support.
    • Would love an official docker image.
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    Alternatives Considered
    ClickHouse, Inc.
    ClickHouse outperforms, especially in costs, since its compression/indexing engines are so smart, and even with very low computing power, you can already perform huge analyses of the data.
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    Open Source
    To be honest, titan is not as popular as Neo4j, though they do the same thing. In my personal opinion, titan has lot of potential, but Neo4j is easier to use. If the organization is big enough, it might choose titan because of its open source nature, and high scalability, but Neo4j comes with a lot of enterprise and community support, better query, better documentation, better instructions, and is also backed by leading tech companies. But titan is very strong when you consider standards. Titan follows gremlin and tinkerpop, both of which will be huge in future as more graph database vendors join the market. If things go really well, maybe Neo4j might have to support gremlin as well.
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    Return on Investment
    ClickHouse, Inc.
    • Queries that used to take more than 2 minutes now take less than 1 second
    • Possibility to analyze use cases in real time (before was impossible)
    • The applications are more complete and the users decisions are better
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    Open Source
    • Steep learning curve. Your engineers would have to spend lots of time learning different components before they feel comfortable.
    • Have to plan ahead. Maybe this is the nature of graph databases, but I found it difficult to change my schemas after I had data in production.
    • It is free, so time is the only resource you have to put in titan.
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