Apache HBase vs. VictoriaMetrics Community

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.

Incentivized

Best suited, where your data is highly cardinal since it does a better job at maintaining it than other competitors. It is also well suited if you are using Prometheus and are looking for something that is less hungry for resources in comparison since the migration would be easier. But in case the company is small and wants a solution which is cheap and relies on built-in visualizations, it is not something that is suited. Although it takes fewer resources than Prometheus, it is still resource-intensive and attracts a high cost for maintenance.

Incentivized

• Scalability. HBase can scale to trillions of records.
• Fast. HBase is extremely fast to scan values or retrieve individual records by key.
• HBase can be accessed by standard SQL via Apache Phoenix.
• Integrated. I can easily store and retrieve data from HBase using Apache Spark.
• It is easy to set up DR and backups.
• Ingest. It is easy to ingest data into HBase via shell, Java, Apache NiFi, Storm, Spark, Flink, Python and other means.

Incentivized

• Easy to configure and manage
• Ready to be configured at cloud and microservices
• Easy to scale vertically and horizontally

Incentivized

• There are very few commands in HBase.
• 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.

Incentivized

• Community and Eco system -> Although it supports the ecosystem of Prometheus, it is still troublesome for someone who's not using Prometheus
• Configuration is not so easy, especially if you are a beginner, you will struggle a bit. Even the documentation is not so welcoming for beginners
• Built-in Visualisation is bare minimal, leading almost everyone to use some other extension/tool

Incentivized

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.

Incentivized

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.

Incentivized

Prometheus only support PromQL and it is very complex with different exporter required for different requirement like Windowsexporter,linixexporter,sqlexporter etc but VictoriaMetrics is very simple comapred to it. VictoriaMetrics support both PromQL and MetricQL and can be integrated with Graphana easily. It is very easy to setup and learn compared to mutiple Prometheus exporters

Incentivized

• 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.

Incentivized

• Lowered our infra costs in comparison with our older tools
• Need minimal effort for migration since it already supports Prometheus ecosystem
• Saved on Storage costs

Incentivized