DBMS > Brytlyt vs. GBase vs. Heroic vs. Microsoft Azure Synapse Analytics vs. RocksDB

System Properties Comparison Brytlyt vs. GBase vs. Heroic vs. Microsoft Azure Synapse Analytics vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

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

Score	0.27
Rank	#292	Overall
	#132	Relational DBMS

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Website

brytlyt.io

www.gbase.cn

github.com/spotify/heroic

azure.microsoft.com/services/synapse-analytics

rocksdb.org

Technical documentation

docs.brytlyt.io

spotify.github.io/heroic

docs.microsoft.com/azure/synapse-analytics

github.com/facebook/rocksdb/wiki

Developer

Brytlyt

General Data Technology Co., Ltd.

Spotify

Microsoft

Facebook, Inc.

Initial release

2016

2004

2014

2016

2013

Current release

5.0, August 2023

GBase 8a, GBase 8s, GBase 8c

9.4.0, June 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

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, Java, Python

Java

C++

Server operating systems

Linux
OS X
Windows

Linux

hosted

Linux

Data scheme

yes

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.

yes

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

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

Standard with numerous extensions

yes

APIs and other access methods

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

ADO.NET
C API
JDBC
ODBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC

C++ API
Java API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C#
Java
PHP

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

user defined functions

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Sharding, horizontal partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

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

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

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

Future of Data Visualization and Agile Business Intelligence
17 May 2021, insideHPC

provided by Google News

General Available: Azure Synapse Runtime for Apache Spark 3.4 is now GA
8 April 2024, Microsoft

Azure Synapse Runtime for Apache Spark 3.2 End of Support
22 March 2024, Microsoft

Azure Synapse vs. Databricks: Data Platform Comparison 2024
26 March 2024, eWeek

Announcing General Availability of Graph Semantics in Kusto
27 May 2024, Microsoft

Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT
18 October 2023, AWS Blog

provided by Google News

AMD EPYC vs. Intel Xeon Cascadelake With Facebook's RocksDB Database
17 October 2019, Phoronix

Pliops Unveils Accelerated Key-Value Store That Boosts RocksDB Performance by 20x at OCP Global Summit
18 October 2022, GlobeNewswire

Did Rockset Just Solve Real-Time Analytics?
25 August 2021, Datanami

Meta’s Velox Means Database Performance Is Not Subject To Interpretation
31 August 2022, The Next Platform

Facebook’s MyRocks Truly Rocks!
21 September 2020, Open Source For You

provided by Google News

Share this page