DBMS > ArcadeDB vs. GeoMesa vs. Qdrant vs. SAP HANA

System Properties Comparison ArcadeDB vs. GeoMesa vs. Qdrant vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Spatial DBMS

Vector DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.02
Rank	#374	Overall
	#52	Document stores
	#38	Graph DBMS
	#56	Key-value stores
	#38	Time Series DBMS

Score	0.78
Rank	#214	Overall
	#4	Spatial DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Website

arcadedb.com

www.geomesa.org

github.com/qdrant/qdrant
qdrant.tech

www.sap.com/products/hana.html

Technical documentation

docs.arcadedb.com

www.geomesa.org/documentation/stable/user/index.html

qdrant.tech/documentation

help.sap.com/hana

Developer

Arcade Data

CCRi and others

Qdrant

SAP

Initial release

2021

2014

2021

2010

Current release

September 2021

5.0.1, July 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Scala

Rust

Server operating systems

All OS with a Java VM

Docker
Linux
macOS
Windows

Appliance or cloud-service

Data scheme

schema-free

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

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

JDBC
ODBC

Supported programming languages

Java

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

Server-side scripts

Stored procedures

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

depending on storage layer

Collection-level replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Eventual Consistency, tunable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Key-based authentication

yes

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