ClickHouse vs. Titan Distributed Graph Database

ClickHouse delivers exceptional speed and performance, positioning it as the top choice for managing large-scale analytical workloads. With a bunch of built-in functions, it empowers analysts to extract maximum insights from data effortlessly. If your scenario is to deal with analytical questions, then ClickHouse is for you, but if you are looking into a transactional database, that's not the case; even their table engines are not made for this.

Incentivized

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.

Incentivized

• 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

Incentivized

• 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.

Incentivized

• Avro data manipulation
• Kafka consistency
• DDL operations errors (by replica configuration)

Incentivized

• 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.

Incentivized

ClickHouse was not compared to them as a competitor but as the ideal partner to complete an information analysis system, providing users with the most complete and efficient tools. Therefore, in this case it was considered that it would be the ideal candidate due to its characteristics compared to the other competitors.

Incentivized

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.

Incentivized

• 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

Incentivized

• 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.

Incentivized