DBMS > Apache Impala vs. GreptimeDB vs. OpenQM vs. searchxml

System Properties Comparison Apache Impala vs. GreptimeDB vs. OpenQM vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

An open source Time Series DBMS built for increased scalability, high performance and efficiency

QpenQM is a high-performance, self-tuning, multi-value DBMS

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

Time Series DBMS

Multivalue DBMS

Native XML DBMS
Search engine

Secondary database models

Document store

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	0.00
Rank	#385	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

impala.apache.org

greptime.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.searchxml.net/category/products

Technical documentation

impala.apache.org/impala-docs.html

docs.greptime.com

www.searchxml.net/support/handouts

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Greptime Inc.

Rocket Software, originally Martin Phillips

informationpartners gmbh

Initial release

2013

2022

1993

2015

Current release

4.1.0, June 2022

3.4-12

1.0

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

GPLv2, extended commercial license available

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++

Rust

C++

Server operating systems

Linux

Android
Docker
FreeBSD
Linux
macOS
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Windows

Data scheme

yes

schema-free, schema definition possible

yes

with some exceptions

schema-free

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

gRPC
HTTP API
JDBC

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

All languages supporting JDBC/ODBC

C++
Erlang
Go
Java
JavaScript

.Net
Basic
C
Java
Objective C
PHP
Python

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Python

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

sychronisation to multiple collections

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

multiple readers, single writer

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.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Simple rights management via user accounts

Access rights can be defined down to the item level

Domain, group and role-based access control at the document level and for application services

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera brings Apache Iceberg data lake format to its Data Platform
30 June 2022, SiliconANGLE News

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

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