The Apache HBase project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable.
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QuestDB
Score 10.0 out of 10
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QuestDB is an open source time series database. It implements SQL and exposes a Postgres wire protocol, a REST API, and supports ingestion with InfluxDB line protocol.
Hbase is well suited for large organizations with millions of operations performing on tables, real-time lookup of records in a table, range queries, random reads and writes and online analytics operations. Hbase cannot be replaced for traditional databases as it cannot support all the features, CPU and memory intensive. Observed increased latency when using with MapReduce job joins.
QuestDB is well suited for any use case where you need to store large amount of data and the performance is the key factor - for both reads and writes. So use cases like market data storage in financial industry, any kind of telemetry, etc.
Stored procedures functionality is not available so it should be implemented.
HBase is CPU and Memory intensive with large sequential input or output access while as Map Reduce jobs are primarily input or output bound with fixed memory. HBase integrated with Map-reduce jobs will result in random latencies.
There's really not anything else out there that I've seen comparable for my use cases. HBase has never proven me wrong. Some companies align their whole business on HBase and are moving all of their infrastructure from other database engines to HBase. It's also open source and has a very collaborative community.
Cassandra os great for writes. But with large datasets, depending, not as great as HBASE. Cassandra does support parquet now. HBase still performance issues. Cassandra has use cases of being used as time series. HBase, it fails miserably. GeoSpatial data, Hbase does work to an extent. HA between the two are almost the same.
We were looking for time series database that will be able to handle L2 market data and came across QuestDB. From the beginning we were impressed how well the QuestDB performs and that it actually significantly outperforms all other open source TSDB on market like InfluxDB, ClickHouse, Timescale, etc. Apart from the excellent performance it is also super easy to use and deploy which makes the experience of using the database very pleasant - we were able to be up and running and storing data within few hours. Topic itself is the QuestDB team that is super responsive on their slack channel and always ready to help with any query. They are constantly improving the product and if there is some missing feature that is blocking you from usage they always try the best to implement such feature asap and release a new version - one of the best support I have ever seen so far in open source community.
As Hbase is a noSql database, here we don't have transaction support and we cannot do many operations on the data.
Not having the feature of primary or a composite primary key is an issue as the architecture to be defined cannot be the same legacy type. Also the transaction concept is not applicable here.
The way data is printed on console is not so user-friendly. So we had to use some abstraction over HBase (eg apache phoenix) which means there is one new component to handle.
