DBMS > Apache Druid vs. H2GIS vs. LevelDB vs. SAP HANA vs. STSdb

System Properties Comparison Apache Druid vs. H2GIS vs. LevelDB vs. SAP HANA vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Spatial extension of H2

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

In-memory, column based data store. Available as appliance or cloud service

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS
Time Series DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

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

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

druid.apache.org

www.h2gis.org

github.com/google/leveldb

www.sap.com/products/hana.html

github.com/STSSoft/STSdb4

Technical documentation

druid.apache.org/docs/latest/design

www.h2gis.org/docs/home

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

help.sap.com/hana

Developer

Apache Software Foundation and contributors

CNRS

Google

SAP

STS Soft SC

Initial release

2012

2013

2011

2010

2011

Current release

29.0.1, April 2024

1.23, February 2021

2.0 SPS07 (April 4, 2023), April 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

LGPL 3.0

Open Source

BSD

commercial

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

Illumos
Linux
OS X
Windows

Appliance or cloud-service

Windows

Data scheme

yes

schema-less columns are supported

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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.

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

.NET Client API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C#
Java

Server-side scripts

Stored procedures

yes

based on H2

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

based on H2

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

yes

based on H2

yes

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