DBMS > Prometheus vs. Transwarp Hippo vs. Yaacomo

System Properties Comparison Prometheus vs. Transwarp Hippo vs. Yaacomo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Open-source Time Series DBMS and monitoring system

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Time Series DBMS

Vector DBMS

Relational DBMS

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

Score	7.92
Rank	#51	Overall
	#2	Time Series DBMS

Score	0.00
Rank	#392	Overall
	#14	Vector DBMS

Website

prometheus.io

www.transwarp.cn/en/subproduct/hippo

yaacomo.com

Technical documentation

prometheus.io/docs

Developer

Q2WEB GmbH

Initial release

2015

2023

2009

Current release

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

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

C++

Server operating systems

Linux
Windows

Linux
macOS

Android
Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

Numeric data only

Vector, Numeric and String

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

RESTful HTTP API

JDBC
ODBC

Supported programming languages

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

C++
Java
Python

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by Federation

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

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.

yes

User concepts

Access control

Role based access control and fine grained access rights

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

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

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

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

My Prometheus is Overwhelmed! Help!
24 July 2021, hackernoon.com

provided by Google News

Share this page