DBMS > H2 vs. Prometheus vs. Qdrant vs. Transbase vs. XTDB

System Properties Comparison H2 vs. Prometheus vs. Qdrant vs. Transbase vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Open-source Time Series DBMS and monitoring system

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

A resource-optimized, high-performance, universally applicable RDBMS

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.h2database.com

prometheus.io

github.com/qdrant/qdrant
qdrant.tech

www.transaction.de/en/products/transbase.html

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

Technical documentation

www.h2database.com/html/main.html

prometheus.io/docs

qdrant.tech/documentation

www.transaction.de/en/products/transbase/features.html

www.xtdb.com/docs

Developer

Thomas Mueller

Qdrant

Transaction Software GmbH

Juxt Ltd.

Initial release

2005

2015

2021

1987

2019

Current release

2.2.220, July 2023

Transbase 8.3, 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

free development license

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

Rust

C and C++

Clojure

Server operating systems

All OS with a Java VM

Linux
Windows

Docker
Linux
macOS
Windows

FreeBSD
Linux
macOS
Solaris
Windows

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

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

Numbers, Strings, Geo, Boolean

yes

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.

Import of XML data possible

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST
JDBC

Supported programming languages

Java

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

by Federation

Collection-level replication

Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

Key-based authentication

fine grained access rights 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

VTEX scales to 150 million metrics using Amazon Managed Service for Prometheus | Amazon Web Services
10 March 2024, AWS Blog

VictoriaMetrics Offers Prometheus Replacement for Time Series Monitoring
17 July 2023, The New Stack

Linux System Monitoring with Prometheus, Grafana, and collectd
1 February 2024, Linux Journal

Consider Grafana vs. Prometheus for your time-series tools
18 October 2021, TechTarget

How to reduce Istio sidecar metric cardinality with Amazon Managed Service for Prometheus | Amazon Web Services
10 October 2023, AWS Blog

provided by Google News

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

Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
16 April 2024, Business Wire

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

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

Why Vector Data Services For AI Are A Moveable Feast
17 April 2024, Forbes

provided by Google News

Share this page