DBMS > Apache Drill vs. GreptimeDB vs. LevelDB vs. PostgreSQL vs. RDF4J

System Properties Comparison Apache Drill vs. GreptimeDB vs. LevelDB vs. PostgreSQL vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Document store
Relational DBMS

Time Series DBMS

Key-value store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

RDF store

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

drill.apache.org

greptime.com

github.com/google/leveldb

www.postgresql.org

rdf4j.org

Technical documentation

drill.apache.org/docs

docs.greptime.com

github.com/google/leveldb/blob/main/doc/index.md

www.postgresql.org/docs

rdf4j.org/documentation

Developer

Apache Software Foundation

Greptime Inc.

Google

PostgreSQL Global Development Group

www.postgresql.org/developer

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2012

2022

2011

1989

1989: Postgres, 1996: PostgreSQL

2004

Current release

1.20.3, January 2023

1.23, February 2021

16.3, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

BSD

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

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Implementation language

Rust

C++

Java

Server operating systems

Linux
OS X
Windows

Android
Docker
FreeBSD
Linux
macOS
Windows

Illumos
Linux
OS X
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

schema-free, schema definition possible

schema-free

yes

RDF Schemas

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

standard with numerous extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP API
JDBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C++

C++
Erlang
Go
Java
JavaScript

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Python

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

partitioning by range, list and (since PostgreSQL 11) by hash

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

other methods possible by using 3rd party extensions

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

with automatic compression on writes

yes

in-memory storage is supported as well

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

User concepts

Access control

Depending on the underlying data source

Simple rights management via user accounts

fine grained access rights according to SQL-standard

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

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.

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