DBMS > Datastax Enterprise vs. Lovefield vs. Realm vs. SAP HANA

System Properties Comparison Datastax Enterprise vs. Lovefield vs. Realm vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector 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	5.93
Rank	#56	Overall
	#4	Wide column stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.datastax.com/products/datastax-enterprise

google.github.io/lovefield

realm.io

www.sap.com/products/hana.html

Technical documentation

docs.datastax.com

github.com/google/lovefield/blob/master/docs/spec_index.md

realm.io/docs

help.sap.com/hana

Developer

DataStax

Google

Realm, acquired by MongoDB in May 2019

SAP

Initial release

2011

2014

2010

Current release

6.8, April 2020

2.1.12, February 2017

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

commercial

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.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

Implementation language

Java

JavaScript

Server operating systems

Linux
OS X

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Android
Backend: server-less
iOS
Windows

Appliance or cloud-service

Data scheme

schema-free

yes

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

SQL-like DML and DDL statements (CQL); Spark SQL

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

JDBC
ODBC

Supported programming languages

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

JavaScript

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

SQLScript, R

Triggers

yes

Using read-only observers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware, advanced replication for edge computing

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

In-Memory realm

yes

User concepts

Access control

Access rights for users can be defined per object

yes

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

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