DBMS > GigaSpaces vs. MySQL vs. Qdrant vs. RocksDB

System Properties Comparison GigaSpaces vs. MySQL vs. Qdrant vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Widely used open source RDBMS

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Key/Value like access via memcached API

Vector DBMS

Key-value store

Secondary database models

Graph DBMS
Search engine

Document store
Spatial DBMS

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

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.gigaspaces.com

www.mysql.com

github.com/qdrant/qdrant
qdrant.tech

rocksdb.org

Technical documentation

docs.gigaspaces.com/latest/landing.html

dev.mysql.com/doc

qdrant.tech/documentation

github.com/facebook/rocksdb/wiki

Developer

Gigaspaces Technologies

Oracle

since 2010, originally MySQL AB, then Sun

Qdrant

Facebook, Inc.

Initial release

2000

1995

2021

2013

Current release

15.5, September 2020

8.4.0, April 2024

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Implementation language

Java, C++, .Net

C and C++

Rust

C++

Server operating systems

Linux
macOS
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Docker
Linux
macOS
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

SQL-99 for query and DML statements

yes

with proprietary extensions

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

C++ API
Java API

Supported programming languages

.Net
C++
Java
Python
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication
Source-replica replication

Collection-level replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

yes

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept

no user groups or roles

Key-based authentication

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