DBMS > Datastax Enterprise vs. Sequoiadb vs. STSdb vs. TigerGraph

System Properties Comparison Datastax Enterprise vs. Sequoiadb vs. STSdb vs. TigerGraph

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Editorial information provided by DB-Engines

Name

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.

NewSQL database with distributed OLTP and SQL

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Wide column store

Document store
Relational DBMS

Key-value store

Graph DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

www.datastax.com/products/datastax-enterprise

www.sequoiadb.com

github.com/STSSoft/STSdb4

www.tigergraph.com

Technical documentation

docs.datastax.com

www.sequoiadb.com/en/index.php?m=Files&a=index

docs.tigergraph.com

Developer

DataStax

Sequoiadb Ltd.

STS Soft SC

Initial release

2011

2013

2011

2017

Current release

6.8, April 2020

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Server: AGPL; Client: Apache V2

Open Source

GPLv2, commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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.

Implementation language

Java

C++

Server operating systems

Linux
OS X

Linux

Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

yes

primitive types and user defined types (classes)

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements (CQL); Spark SQL

SQL-like query language

SQL-like query language (GSQL)

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

proprietary protocol using JSON

.NET Client API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C++
Java
PHP
Python

C#
Java

C++
Java

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware, advanced replication for edge computing

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomicity and isolation are supported for single operations

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users can be defined per object

simple password-based access control

Role-based access control

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more

Licensing and pricing models

Annual subscription
» more

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