DBMS > LevelDB vs. Realm vs. SAP HANA vs. Spark SQL vs. SwayDB

System Properties Comparison LevelDB vs. Realm vs. SAP HANA vs. Spark SQL vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

github.com/google/leveldb

realm.io

www.sap.com/products/hana.html

spark.apache.org/sql

swaydb.simer.au

Technical documentation

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

realm.io/docs

help.sap.com/hana

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Google

Realm, acquired by MongoDB in May 2019

SAP

Apache Software Foundation

Simer Plaha

Initial release

2011

2014

2010

2014

2018

Current release

1.23, February 2021

2.0 SPS07 (April 4, 2023), April 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

BSD

Open Source

commercial

Open Source

Apache 2.0

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Scala

Server operating systems

Illumos
Linux
OS X
Windows

Android
Backend: server-less
iOS
Windows

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
Java

with Android only
Objective-C
React Native
Swift

Java
Python
R
Scala

Java
Kotlin
Scala

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

SQLScript, R

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

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

In-Memory realm

yes

User concepts

Access control

yes

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