DBMS > Apache Impala vs. mSQL vs. Prometheus vs. ToroDB vs. Transwarp Hippo

System Properties Comparison Apache Impala vs. mSQL vs. Prometheus vs. ToroDB vs. Transwarp Hippo

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

mSQL (Mini SQL) is a simple and lightweight RDBMS

Open-source Time Series DBMS and monitoring system

A MongoDB-compatible JSON document store, built on top of PostgreSQL

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

Primary database model

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

impala.apache.org

hughestech.com.au/products/msql

prometheus.io

github.com/torodb/server

www.transwarp.cn/en/subproduct/hippo

Technical documentation

impala.apache.org/impala-docs.html

prometheus.io/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Hughes Technologies

8Kdata

Initial release

2013

1994

2015

2016

2023

Current release

4.1.0, June 2022

4.4, October 2021

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free licenses can be provided

Open Source

Apache 2.0

Open Source

AGPL-V3

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++

Java

C++

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

All OS with a Java 7 VM

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

yes

string, integer, double, boolean, date, object_id

Vector, Numeric and String

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

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Delphi
Java
Perl
PHP
Tcl

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

C++
Java
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes

by Federation

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users and roles

Role based access control and fine grained access rights

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