DBMS > EsgynDB vs. NSDb vs. Sequoiadb vs. TerarkDB vs. ToroDB

System Properties Comparison EsgynDB vs. NSDb vs. Sequoiadb vs. TerarkDB vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

NewSQL database with distributed OLTP and SQL

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Time Series DBMS

Document store
Relational DBMS

Key-value store

Document store

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

www.esgyn.cn

nsdb.io

www.sequoiadb.com

github.com/bytedance/terarkdb

github.com/torodb/server

Technical documentation

nsdb.io/Architecture

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

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Esgyn

Sequoiadb Ltd.

ByteDance, originally Terark

8Kdata

Initial release

2015

2017

2013

2016

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Server: AGPL; Client: Apache V2

commercial

restricted open source version available

Open Source

AGPL-V3

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.

Implementation language

C++, Java

Java, Scala

C++

Java

Server operating systems

Linux

Linux
macOS

Linux

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

yes

oid, date, timestamp, binary, regex

yes

string, integer, double, boolean, date, object_id

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

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

proprietary protocol using JSON

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java
Scala

.Net
C++
Java
PHP
Python

C++
Java

Server-side scripts

Stored procedures

Java Stored Procedures

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

fine grained access rights according to SQL-standard

simple password-based access control

Access rights for users and roles

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