DBMS > EsgynDB vs. H2GIS vs. LMDB vs. Qdrant vs. Sadas Engine

System Properties Comparison EsgynDB vs. H2GIS vs. LMDB vs. Qdrant vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

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

Spatial extension of H2

A high performant, light-weight, embedded key-value database library

A high-performance vector database with neural network or semantic-based matching

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Secondary database models

Relational DBMS

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

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	0.05
Rank	#372	Overall
	#7	Spatial DBMS

Score	2.33
Rank	#118	Overall
	#21	Key-value stores

Score	1.23
Rank	#171	Overall
	#6	Vector DBMS

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Website

www.esgyn.cn

www.h2gis.org

www.symas.com/symas-embedded-database-lmdb

github.com/qdrant/qdrant
qdrant.tech

www.sadasengine.com

Technical documentation

www.h2gis.org/docs/home

www.lmdb.tech/doc

qdrant.tech/documentation

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Esgyn

CNRS

Symas

Qdrant

SADAS s.r.l.

Initial release

2015

2013

2011

2021

2006

Current release

0.9.32, January 2024

8.0

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

Open Source

Apache Version 2.0

commercial

free trial version available

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

Rust

C++

Server operating systems

Linux

Linux
Unix
Windows

Docker
Linux
macOS
Windows

AIX
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

JDBC
ODBC
Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

based on H2

none

Collection-level 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

Eventual Consistency, tunable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

yes

based on H2

Key-based authentication

Access rights for users, groups and roles according to SQL-standard

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

Threat Actors Exploit Multiple Vulnerabilities in Ivanti Connect Secure and Policy Secure Gateways
29 February 2024, CISA

Automating SAP S/4HANA Migration with IT-Conductor, BGP Managed Services, and AWS | Amazon Web Services
22 August 2023, AWS Blog

The Tom Brady Data Biography
8 September 2023, StatsBomb

Akamai launches managed database service – Blocks and Files
25 April 2022, Blocks and Files

The Lightning Memory-mapped Database
2 March 2016, InfoQ.com

provided by Google News

Qdrant offers managed vector database for hybrid clouds
16 April 2024, InfoWorld

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Qdrant launches first vector database as a managed hybrid cloud
16 April 2024, VentureBeat

Open-source vector database Qdrant launches hybrid cloud for enterprise AI apps
16 April 2024, SiliconANGLE News

Qdrant Hybrid Cloud is Now Available for OCI Customers: Managed Vector Search Engine for Data-Sensitive AI ...
16 April 2024, blogs.oracle.com

provided by Google News

Share this page