![]() ![]() ![]() However, I'm not totally sure about HA, Graph data backup, cross-data center support. Such cases will be analyzed by our ML-algorithm and implemented in our database, which will improve this summary. If you think that some of this information is not accurate, please let us know about it and provide any supporting evidences if possible. I still need to evaluate if it fulfills our need as a graph DB though, I also learned that SQL server 2019 is still a new player in the market and attempts to fit a graph-like query on top of a relational model (with node and edge tables). Get started with Metabase Be up and running in minutes Metabase Cloud The fastest way to try Metabase. This summary is composed by our algorithm based on the analysis of the deals. I'm inclining towards SQL server 2019 graph as we already use SQL server extensively as relational database & have all the HA and cross data center replication setup readily available. We currently use Redis as a cache & SQL server 2019 as RDBMS. GraphQL, Klaviyo, Heap Analytics, Google Analytics, StitchData, Metabase, Shopify, Stripe, VWO. Also, due to the nature of data & org policies, using a cloud-based solution won't be a viable choice. Metabase Dashboard Metabase is a good, popular open-source BI tool that anyone can quickly install on your local environment to get a simple BI system up and running. While Neo4j is a much-matured solution in general, I'm not accounting for it due to the cost & introduction of a new stack in the ecosystem. One of the key criteria is high availability and cross data center replication of data. Metabase comes with everything you need for your team to start exploring data. I'm evaluating the use of RedisGraph vs Microsoft SQL Server 2019 graph features to build a social graph. A familiar, intutive interface for SQL beginners and non-technical users Advanced options for power users 15+ built-in data visualizations Easy options for sharing and embedding Ready to go.
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