DBMS > Geode vs. PouchDB vs. Qdrant vs. SQLite vs. XTDB

System Properties Comparison Geode vs. PouchDB vs. Qdrant vs. SQLite vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

JavaScript DBMS with an API inspired by CouchDB

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

Widely used embeddable, in-process RDBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

geode.apache.org

pouchdb.com

github.com/qdrant/qdrant
qdrant.tech

www.sqlite.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

geode.apache.org/docs

pouchdb.com/guides

qdrant.tech/documentation

www.sqlite.org/docs.html

www.xtdb.com/docs

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Apache Software Foundation

Qdrant

Dwayne Richard Hipp

Juxt Ltd.

Initial release

2002

2012

2021

2000

2019

Current release

1.1, February 2017

7.1.1, June 2019

3.45.3 (15 April 2024), April 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache Version 2.0

Open Source

Public Domain

Open Source

MIT License

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

Java

JavaScript

Rust

Clojure

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

server-less, requires a JavaScript environment (browser, Node.js)

Docker
Linux
macOS
Windows

server-less

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

yes

not rigid because of 'dynamic typing' concept.

yes, extensible-data-notation format

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

via views

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

SQL-like query language (OQL)

yes

SQL-92 is not fully supported

limited SQL, making use of Apache Calcite

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

HTTP REST
JDBC

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

JavaScript

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

View functions in JavaScript

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Collection-level replication

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights per client and object definable

Key-based authentication

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