Posts Tagged Exasol
The TPC-H Benchmark is for Decision Support Systems. It’s described very detailed on the TPC.ORG site, but you may find it quite an effort to generate the data and prepare the SQL for table creation and reporting.
At least I did, which is why I thought having that all ready for download and run would be helpful.
What I have prepared for Oracle and for Exasol is:
- The data files (CSV format) for the 1 GB TPC-H
- The DDL for the TPC-H tables
- The loader commands to populate these tables
- The 22 queries for the TPC-H benchmark
You can download it here:
The data volume is of course quite small for a production data warehouse but ideal for quick testing and self-education. I’m using it together with VirtualBox and VMs on my notebook with 16 GB memory.
See here for a demo – I’m setting up the TPC-H for both Oracle and Exasol and then I do a comparison:
Some remarks about the comparison:
I’m an Exasol employee and the outcome is very positive for Exasol.
Never the less, I tried to do a fair comparison. It’s just running the pure 22 SELECT statements, no tuning, no tweaking of the Exasol database or the underlying VM.
The Oracle version is quite recent (18.3) but not the most recent, same with the Exasol version (6.2), not the just released Exasol 7.0.
As you can see, the Exasol database is out of the box about 6 times faster than the Oracle database for the same workload having the same hardware resources – without any tuning.
I suppose you could get better performance from Oracle for the 22 queries with some effort, like analyzing the workload, adding indexes of the certain available types, partitioning the tables, adding SQL Profiles and Optimizer Directives etc.
The point is, that’s all not required with Exasol. I just run the workload twice and everything is self-optimized afterwards.
You could call this an autonomous database 😉
It’s totally easy to reproduce the test for yourself: Just download our free Community Edition; it’s what I’m using in this benchmark.
Keep in mind that this is a Decision Support System benchmark with an analytical workload. Oracle looks much better in a comparison with an OLTP workload.
But for analytics: Exasol stands behind nobody.
To all the other vendor’s presales consultants out there who encounter us on a PoC: Good luck 🙂
Isn’t it nice if you can make an impact with your tweets and posts? That’s what I thought today while investigating our online learning registrations.
As you may know, Exasol offers free online learning – recently also combined with free certification. We have also recently changed our course curriculum to better suit customer demands.
Together with very many IT people being in home office, that all leads to quite high numbers in registrations to our online learning platform called Exacademy: 617 in 2020 so far.
That’s many for a still quite small training & certification department like ours, and we couldn’t possibly educate that many customers with instructor-led courses.
Today, I looked at the Exacademy registrations per day:
Roughly 10 per day on average, but 74 on March 27th. What happend that day? Now I looked at my tweets from March:
Tweet analytics shows:
Looks like these 2000 impressions contributed to the unusual high number of Exacademy enrollments, which makes me quite happy 🙂
By the way, we provided 200 free certification exams so far. Get your free Exasol online training together with a free certification now: training.exasol.com
This is the second part of the mini-series Exasol on AWS. Here’s the first part.
Cloud UI is an extension to EXAoperation that makes it easy for you to
- Scale up & down
- Increase storage capacity
- Scale out by adding nodes to the cluster
Cloud UI can be reached by adding the port number 8835 to the URL of your License Server and uses the same credentials as EXAoperation.
Scale down to m5.large with Cloud UI
Depending on the load you get on your Exasol cluster, you can scale up your data nodes to more powerful EC2 instances if load is high and scale down to less expensive EC2 instances with lower user demands.
I started my little cluster with r5.large instances. Now I want to scale down to m5.large. Enter Cloud UI:
You see on the right site that scaling down to m5.large reduces both available memory and costs. I click on APPLY now and confirm the pop-up coming next with EXECUTE. The following steps the system goes through can be monitored in EXAoperation:
Notice that the database got restarted during that process.
Scale out by adding data nodes
I want to expand my present 1+0 cluster to a 2+1 cluster. First I add another active node:
As you see, this doesn’t only increase the overall avaible memory but also the compute power. Storage capacity is usually also increased when adding a node. In this particular case not, though, because I will also go from redundancy 1 to redundancy 2.
The log looks like this now:
My one node cluster did use redundancy 1, now I want to change that to redundancy 2. That step is of course not required when you started with a multi-node cluster using redundancy 2 already. See here for more details about redundancy in Exasol.
To increase redundancy, I go to the EXAstorage page of EXAoperation:
The new EC2 instance for the new data node can be renamed like this:
That makes it easier to identify the nodes, for example when associating elastic IPs to them. I do that now for n12 in the same way I did it with n11 before.
The elastic IPs of the data nodes must then be entered into the connection details of clients like DbVisualizer in this example:
After having added a new active node, that node is initially empty unless REORGANIZE operations are done. For example a REORGANIZE DATABASE:
I have a 2+0 cluster now: Mirrored segments on two active nodes but no reserve node.
Adding reserve nodes
To get a 2+1 cluster, I need to add a reserve node. Again, that’s quite easy to do with Cloud UI:
Within about 10 Minutes, the log should show something like this:
Notice that there was no database restart this time. The new node should get renamed and have a new elastic IP associated as shown before. Also that IP needs to be added to client connection details. See here if you wonder what reserve nodes are good for.
Now that I have got a 2+1 Exasol cluster running on AWS, I’m ready to demonstrate what happens if one node fails. That will be the next part of this series 🙂