DBMS > BigObject vs. Brytlyt vs. H2 vs. Teradata

System Properties Comparison BigObject vs. Brytlyt vs. H2 vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	0.27
Rank	#292	Overall
	#132	Relational DBMS

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	41.47
Rank	#22	Overall
	#15	Relational DBMS

Website

Technical documentation

docs.bigobject.io

docs.brytlyt.io

www.h2database.com/html/main.html

docs.teradata.com

Developer

BigObject, Inc.

Brytlyt

Thomas Mueller

Teradata

Initial release

2015

2016

2005

1984

Current release

5.0, August 2023

2.2.220, July 2023

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Cloud-based only

Only available as a cloud 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

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X
Windows

All OS with a Java VM

hosted
Linux

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.

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL 2016 + extensions

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

JDBC
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Java

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

Lua

user defined functions

in PL/pgSQL

Java Stored Procedures and User-Defined Functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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Recent citations in the news

Opensignal Announces Acquisition of Brytlyt GPU-based Data Analytics & Visualization Technology
5 June 2024, PR Web

Brytlyt releases version 5.0, introducing a more intuitive, intelligent and flexible analytics platform
1 August 2023, PR Newswire

Bringing GPUs To Bear On Bog Standard Relational Databases
26 February 2018, The Next Platform

London’s Brytlyt raises €4.4 million for its data analytics and visualisation technology
22 December 2021, EU-Startups

Brytlyt Unleashes Serverless GPU-Acceleration for Analytics
15 September 2021, PR Newswire

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20 September 2024, Seeking Alpha

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18 September 2024, insideBIGDATA

Teradata ClearScape Analytics update targets ROI on AI, ML
17 September 2024, TechTarget

provided by Google News

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