DBMS > Brytlyt vs. HEAVY.AI vs. Lovefield vs. SAP HANA

System Properties Comparison Brytlyt vs. HEAVY.AI vs. Lovefield vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

Relational DBMS

Secondary database models

Spatial 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	0.38
Rank	#279	Overall
	#126	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	45.84
Rank	#22	Overall
	#16	Relational DBMS

Website

brytlyt.io

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

www.sap.com/products/hana.html

Technical documentation

docs.brytlyt.io

docs.heavy.ai

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

help.sap.com/hana

Developer

Brytlyt

HEAVY.AI, Inc.

Google

SAP

Initial release

2016

2014

2010

Current release

5.0, August 2023

5.10, January 2022

2.1.12, February 2017

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

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.

Implementation language

C, C++ and CUDA

C++ and CUDA

JavaScript

Server operating systems

Linux
OS X
Windows

Linux

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

tested with Chrome, Firefox, IE, Safari

Appliance or cloud-service

Data scheme

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.

yes

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

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

JDBC
ODBC
Thrift
Vega

JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

SQLScript, R

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

none

yes

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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