DBMS > EJDB vs. Transwarp Hippo vs. Transwarp KunDB vs. Transwarp StellarDB

System Properties Comparison EJDB vs. Transwarp Hippo vs. Transwarp KunDB vs. Transwarp StellarDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

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

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	0.00
Rank	#385	Overall
	#16	Vector DBMS

Score	0.04
Rank	#362	Overall
	#154	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Website

github.com/Softmotions/ejdb

www.transwarp.cn/en/subproduct/hippo

www.transwarp.cn/en/product/kundb

www.transwarp.cn/en/product/stellardb

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

Developer

Softmotions

Transwarp

Initial release

2012

2023

Current release

1.0, May 2023

License

Commercial or Open Source

Open Source

GPLv2

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.

Implementation language

C++

Server operating systems

server-less

Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

Vector, Numeric and String

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

yes

SQL-like query language

APIs and other access methods

in-process shared library

RESTful HTTP API

OpenCypher

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C++
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

Role based access control and fine grained access rights

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

10 top vector database options for similarity searches
8 August 2024, TechTarget

provided by Google News

Share this page