ArangoDB is a distributed free and open-source database with a flexible data model for graphs, documents, and key-values. Its supporters state that developers can build high performance applications on top of ArangoDB using a convenient SQL-like query language or JavaScript extensions.
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Astra DB
Score 8.2 out of 10
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Astra DB from DataStax is a vector database for developers that need to get accurate Generative AI applications into production, fast.
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Pricing
ArangoDB
Astra DB
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
ArangoDB
Astra DB
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
ArangoDB
Astra DB
Features
ArangoDB
Astra DB
Vector Database
Comparison of Vector Database features of Product A and Product B
Use cases provided by default are good and can be improve better using Machine Learning and AI. AQL query language is very simple and efficient in use if anyone using SQL can quickly learn AQL Language.
Developers can easily map the database and can access various patterns like search, ranking.
JSON and semantic search is the latest and next-generation technology to implement to access and extract large datasets.
We use Astra DB to improve our management systems. Storing data has become hassle-free and quite simple. When launching a Cassandra-based cloud application, Astra DB is exactly what you need. In addition to the standard training programs and videos, the extended support and training require significant additional effort to activate and cover which I feel is a bit more tedious task.
We need to be able to process a lot of data (our biggest clients process hundreds of milions of transactions every month). However, it is not only the amount of data, it is also an unpredictable patterns with spikes occuring at different points of time - something athat Astra is great at.
Our processing needs to be extremaly fast. Some of our clients use our enrichment in a synchronous way, meaning that any delay in processing is holding up the whole transaction lifecycle and can have a major impact on the client. Astra is very fast.
A close collaboration with GCP makes our life very easy. All of our technology sits in Google Cloud, so having Astra in there makes it a no-brainer solution for us.
Astra DB might be difficult to understand for people who are unfamiliar with Apache Cassandra. Improving the initial experience for newcomers, as well as offering better documentation and lessons, might be advantageous.
The Astra DB ecosystem may be enhanced by expanding the ecosystem of plugins, integrations, and community-contributed solutions.
Their response time is fast, in case you do not contact them during business hours, they give a very good follow-up to your case. They also facilitate video calls if necessary for debugging.
We also (briefly) considered building in-house. We wanted to avoid complex "Frankenstein" architectures. Combining Pinecone with another NoSQL datastore like DynamoDB would have increased complexity. A single-managed platform (Astra DB) enabled architectural simplicity and strong reliability, allowing Maester’s development team to prioritize high-value, customer-facing features
We are well aware of the Cassandra architecture and familiar with the open source tooling that Datastax provides the industry (K8sSandra / Stargate) to scale Cassandra on Kubernetes.
Having prior knowledge of Cassandra / Kubernetes means we know that under the hood Astra is built on infinitely scalable technologies. We trust that the foundations that Astra is built on will scale so we know Astra will scale.
Database growth planning is less of a concern with Astra, as it scales automatically.
Currently, they lack fine-grained security at the table level. I suspect that will change over time.
If your load has peaks and valleys; Astra enables only paying for Reads/Writes; thus you do not need to pay for large servers to support peaks in load.
