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.
$0.69
per hour
Azure SQL Database
Score 8.9 out of 10
N/A
Azure SQL Database is Microsoft's relational database as a service (DBaaS).
Well-Suited Scenarios: Real-Time Analytics: Financial trading platforms requiring instant insights. Operational Dashboards: Retail businesses monitoring live sales. IoT Data Processing: Smart device monitoring with high data ingestion. Fraud Detection: Banks detect suspicious transactions instantly. Less Appropriate Scenarios: Archival Storage: Cold data storage with infrequent access. Low-Volume Workloads: Small-scale apps with minimal data processing needs. Complex ETL Pipelines: Heavy data transformations without real-time demands.
Your upcoming app can be built faster on a fully managed SQL database and can be moved into Azure with a few to no application code changes. Flexible and responsive server less computing and Hyperscale storage can cope with your changing requirements and one of the main benefits is the reduction in costs, which is noticeable.
Scalability is #1: if it used to be an almost no-win endeavour to try to modernize your server or migrate to other hardware, with Azure SQL Database it becomes a press of a button.
All the tools simply work after you are on Azure SQL Database.
The applications do not need changes in order to start using Azure SQL Database.
Hybrid Cloud scenarios will work.
Clustering and failover - already there.
You can start monitoring the use and extract performance insights in a new way in Azure.
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.
A little slow on processing complex or large Views. We use a lot of Views to feed our BI system, and the processing time could see some improvement, IMHO.
Additional monitoring components would be nice too, automating some built in performance measurement tools would be a nice feature.
Price can always be improved as well. It’s not bad, but room for improvement.
[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.
When it comes to ingestion speed, SingleStore is probably at the top. Being able to create pipelines using SQL to ingest data from S3, Kafka, and other sources, is a great advantages. This means you can dynamically ingest data by customizing your SQL queries. SingleStore pipelines are pretty sophisticated, yet very simple. Few lines of codes and you are ingesting data, while still able to perform analytical queries on your billions of row tables.
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 give the support a high rating simply because every time we've had issues or questions, representatives were in contact with us quickly. Without fail, our issues/questions were handled in a timely matter. That kind of response is integral when client data integrity and availability is in question. There is also a wealth of documentation for resolving issues on your own.
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.
Reduces database sprawl, ETL costs, infrastructure expenses, etc. Supports horizontal scaling, unlike PostgreSQL & Aurora, and real-time analytics and fast transactions (HTAP), unlike Snowflake & ClickHouse.Handles high-volume workloads with thousands of concurrent queries. No need for ETL processes, unlike BigQuery & Snowflake. Works with JSON, relational, and key-value data, unlike ClickHouse.
Oracle Database is "the" serious database. There really is no competition in that field. SQL Database would be a serious competitor through the ease of implementation and the "no maintenance," but since it's too expensive for "normal" use (medium to small applications), it just priced itself out of the market, so to speak. Nevertheless, we do have 2 or 3 large applications that are highly integrated in azure, and for those it's just too easy to use SQL Database instead of the on premise Oracle Database with VPN gateways etcetera.
Lower operational complexity - Installation and maintenance is pretty easy
Object scale when used can compete with Traditional Warehouse Systems like Teradata, Netezza, Greenplum
Adds lot of value to the business like couple of operations which never worked in traditional DBMS including HANA, Oracle In Memory, SQL Server In Memory just flew in SingleStore
We don't need a dedicated SQL dba because so many of the database maintenance operations are managed. A huge positive not only in budget but time constraints.
The ability to scale quickly is the biggest positive as our data needs change constantly.
Easy to migrate from legacy tools and systems, saving us on the need for redevelopment.
