DBMS > Qdrant vs. Realm vs. RocksDB vs. Spark SQL vs. STSdb

System Properties Comparison Qdrant vs. Realm vs. RocksDB vs. Spark SQL vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

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

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

github.com/qdrant/qdrant
qdrant.tech

realm.io

rocksdb.org

spark.apache.org/sql

github.com/STSSoft/STSdb4

Technical documentation

qdrant.tech/documentation

realm.io/docs

github.com/facebook/rocksdb/wiki

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Qdrant

Realm, acquired by MongoDB in May 2019

Facebook, Inc.

Apache Software Foundation

STS Soft SC

Initial release

2021

2014

2013

2014

2011

Current release

9.2.1, May 2024

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

Apache 2.0

Open Source

GPLv2, commercial license 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

Rust

C++

Scala

Server operating systems

Docker
Linux
macOS
Windows

Android
Backend: server-less
iOS
Windows

Linux

Linux
OS X
Windows

Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

Numbers, Strings, Geo, Boolean

yes

primitive types and user defined types (classes)

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 DML and DDL statements

APIs and other access methods

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

C++ API
Java API

JDBC
ODBC

.NET Client API

Supported programming languages

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

.Net
Java

with Android only
Objective-C
React Native
Swift

C
C++
Go
Java
Perl
Python
Ruby

Java
Python
R
Scala

C#
Java

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Collection-level replication

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency, tunable consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

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.

yes

In-Memory realm

yes

User concepts

Access control

Key-based authentication

yes

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