DBMS > Datastax Enterprise vs. TinkerGraph vs. Valentina Server
System Properties Comparison Datastax Enterprise vs. TinkerGraph vs. Valentina Server
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|Editorial information provided by DB-Engines
|Datastax Enterprise Xexclude from comparison
|TinkerGraph Xexclude from comparison
|Valentina Server Xexclude from comparison
|DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.
|A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
|Object-relational database and reports server
|Primary database model
|Wide column store
|Secondary database models
|6.8, April 2020
|License Commercial or Open Source
|Open Source Apache 2.0
|Cloud-based only Only available as a cloud service
|DBaaS offerings (sponsored links) Database as a Service
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|Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
|Server operating systems
|Typing predefined data types such as float or date
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.
|SQL Support of SQL
|SQL-like DML and DDL statements (CQL); Spark SQL
|APIs and other access methods
|Proprietary protocol CQL (Cassandra Query Language)
TinkerPop Gremlin with DSE Graph
|Supported programming languages
|Server-side scripts Stored procedures
|Partitioning methods Methods for storing different data on different nodes
|Sharding no "single point of failure"
|Replication methods Methods for redundantly storing data on multiple nodes
|configurable replication factor, datacenter aware, advanced replication for edge computing
|MapReduce Offers an API for user-defined Map/Reduce methods
|Consistency concepts Methods to ensure consistency in a distributed system
Tunable Consistency consistency level can be individually decided with each write operation
|Foreign keys Referential integrity
|yes Relationships in graphs
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data
|no Atomicity and isolation are supported for single operations
|Concurrency Support for concurrent manipulation of data
|Durability Support for making data persistent
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.
|User concepts Access control
|Access rights for users can be defined per object
|fine grained access rights according to SQL-standard
|More information provided by the system vendor
|DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
|Supporting the following application requirements: Zero downtime - Built on Apache...
|Typical application scenarios
|Applications that must be massively and linearly scalable with 100% uptime and able...
|Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
|Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
|Licensing and pricing models
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