DBMS > Datastax Enterprise vs. EJDB vs. Sequoiadb
System Properties Comparison Datastax Enterprise vs. EJDB vs. Sequoiadb
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|Editorial information provided by DB-Engines|
|Name||Datastax Enterprise Xexclude from comparison||EJDB Xexclude from comparison||Sequoiadb Xexclude from comparison|
|Description||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.||Embeddable document-store database library with JSON representation of queries (in MongoDB style)||NewSQL database with distributed OLTP and SQL|
|Primary database model||Wide column store||Document store||Document store|
|Secondary database models||Document store|
|Current release||6.8, April 2020|
|License Commercial or Open Source||commercial||Open Source GPLv2||Open Source Server: AGPL; Client: Apache V2|
|Cloud-based only Only available as a cloud service||no||no||no|
|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||Linux|
|Typing predefined data types such as float or date||yes||yes string, integer, double, bool, date, object_id||yes oid, date, timestamp, binary, regex|
|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.||no||no|
|SQL Support of SQL||SQL-like DML and DDL statements (CQL); Spark SQL||no||SQL-like query language|
|APIs and other access methods||Proprietary protocol CQL (Cassandra Query Language)|
TinkerPop Gremlin with DSE Graph
|in-process shared library||proprietary protocol using JSON|
|Supported programming languages||C|
|Partitioning methods Methods for storing different data on different nodes||Sharding no "single point of failure"||none||Sharding|
|Replication methods Methods for redundantly storing data on multiple nodes||configurable replication factor, datacenter aware, advanced replication for edge computing||none||Source-replica replication|
|MapReduce Offers an API for user-defined Map/Reduce methods||yes||no||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency|
Tunable Consistency consistency level can be individually decided with each write operation
|Foreign keys Referential integrity||no||no typically not needed, however similar functionality with collection joins possible||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||no Atomicity and isolation are supported for single operations||no||Document is locked during a transaction|
|Concurrency Support for concurrent manipulation of data||yes||yes Read/Write Locking||yes|
|Durability Support for making data persistent||yes||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||yes||no|
|User concepts Access control||Access rights for users can be defined per object||no||simple password-based access control|
|More information provided by the system vendor|
|Specific characteristics||DataStax Enterprise is scale-out data infrastructure for enterprises that need to...|
|Competitive advantages||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...|
|Key customers||Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...|
|Market metrics||Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...|
|Licensing and pricing models||Annual subscription|
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