DBMS > GreptimeDB vs. MarkLogic vs. OpenQM vs. Oracle Berkeley DB

System Properties Comparison GreptimeDB vs. MarkLogic vs. OpenQM vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines

Name

Description

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

Operational and transactional Enterprise NoSQL database

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

Widely used in-process key-value store

Primary database model

Time Series DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Multivalue DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Score	4.15
Rank	#70	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#8	Search engines

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Website

greptime.com

www.progress.com/marklogic

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

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

docs.greptime.com

www.progress.com/marklogic/documentation

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Greptime Inc.

MarkLogic Corp.

Rocket Software, originally Martin Phillips

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2022

2001

1993

1994

Current release

11.0, December 2022

3.4-12

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

GPLv2, extended commercial license available

Open Source

commercial license available

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

Rust

C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free, schema definition possible

schema-free

Schema can be enforced

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92

yes

SQL interfaced based on SQLite is available

APIs and other access methods

gRPC
HTTP API
JDBC

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

Supported programming languages

C++
Erlang
Go
Java
JavaScript

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
Basic
C
Java
Objective C
PHP
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

Python

yes

via XQuery or JavaScript

yes

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

can act as a resource manager in an XA/JTA transaction

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, with Range Indexes

yes

User concepts

Access control

Simple rights management via user accounts

Role-based access control at the document and subdocument levels

Access rights can be defined down to the item level

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

Conferences, events and webinars

more DBMS events

Progress MarkLogic World
Washington DC, 23-25 September 2024

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