Exasol, from the company of the same name in Nuremberg, is presented by the vendor as a high-performance in-memory analytics database that aims to transform how organizations works with data, on-premises, in the cloud or both.
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SingleStore
Score 8.2 out of 10
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SingleStore aims to enable organizations to scale from one to one million customers, handling SQL, JSON, full text and vector workloads in one unified platform.
We looked at some others too, but was 5 yrs ago so I don't recall the list. Exasol had the best performance per cost, outstanding performance, and was easy to evaluate. Even their community addition running on my laptop was faster than our existing reporting solution.
I can only compare it with Exasol, which I have used a similar base, which manages the Hadoop scheme and is very similar to SingleStore. SingleStore has many advantages: being in the cloud, with just a couple of clicks I can increase the capacity, the configuration is super …
Exasol is suited to applications requiring fewer & larger queries (reporting/data analytics/business intelligence tools). Its per-query overhead makes it unsuitable as an operational database (those are optimized for many & smaller queries.)
Good for Applications needing instant insights on large, streaming datasets. Applications processing continuous data streams with low latency. When a multi-cloud, high-availability database is required When NOT to Use Small-scale applications with limited budgets Projects that do not require real-time analytics or distributed scaling Teams without experience in distributed databases and HTAP architectures.
It does not release a patch to have back porting; it just releases a new version and stops support; it's difficult to keep up to that pace.
Support engineers lack expertise, but they seem to be improving organically.
Lacks enterprise CDC capability: Change data capture (CDC) is a process that tracks and records changes made to data in a database and then delivers those changes to other systems in real time.
For enterprise-level backup & restore capability, we had to implement our model via Velero snapshot backup.
I gave it 9/10 instead of 10/10 only because it lacks in a few advanced enterprise features that require manual workarounds. Otherwise our users have had no problem getting up to speed with it (other than SQL syntax issues that are specific to it, but that's true of any DB)
[Until it is] supported on AWS ECS containers, I will reserve a higher rating for SingleStore. Right now it works well on EC2 and serves our current purpose, [but] would look forward to seeing SingleStore respond to our urge of feature in a shorter time period with high quality and security.
SingleStore excels in real-time analytics and low-latency transactions, making it ideal for operational analytics and mixed workloads. Snowflake shines in batch analytics and data warehousing with strong scalability for large datasets. SingleStore offers faster data ingestion and query execution for real-time use cases, while Snowflake is better for complex analytical queries on historical data.
I have had only positive experiences with their support. They are fast, knowledgeable, and courteous. Online support requests get picked up within hours. I've only once had to use their hotline and that was for an emergency. There was even one minor non-security bug report that I reported and which they fixed in the following week's minor release. I was quite impressed.
The support deep dives into our most complexed queries and bizarre issues that sometimes only we get comparing to other clients. Our special workload (thousands of Kafka pipelines + high concurrency of queries). The response match to the priority of the request, P1 gets immediate return call. Missing features are treated, they become a client request and being added to the roadmap after internal consideration on all client needs and priority. Bugs are patched quite fast, depends on the impact and feasible temporary workarounds. There is no issue that we haven't got a proper answer, resolution or reasoning
We allowed 2-3 months for a thorough evaluation. We saw pretty quickly that we were likely to pick SingleStore, so we ported some of our stored procedures to SingleStore in order to take a deeper look. Two SingleStore people worked closely with us to ensure that we did not have any blocking problems. It all went remarkably smoothly.
Exasol have the best performance by far in analytical queries (DW/BI). Compared to the other database we use much less time on maintenance, actually almost 0 time on indexes distributing data on nodes etc. The system just works out-of-box as long as you have memory enough
Greenplum is good in handling very large amount of data. Concurrency in Greenplum was a major problem. Features available in SingleStore like Pipelines and in memory features are not available in Greenplum. Gemfire was not scaling well like SingleStore. Support of both Greenplum and Gemfire was not good. Product team did not help us much like the ones in SingleStore who helped us getting started on our first cluster very fast.
As the overall performance and functionality were expanded, we are able to deliver our data much faster than before, which increases the demand for data.
Metadata is available in the platform by default, like metadata on the pipelines. Also, the information schema has lots of metadata, making it easy to load our assets to the data catalog.