DBMS > GBase vs. Heroic vs. SQream DB vs. SwayDB vs. TimesTen

System Properties Comparison GBase vs. Heroic vs. SQream DB vs. SwayDB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

a GPU-based, columnar RDBMS for big data analytics workloads

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

In-Memory RDBMS compatible to Oracle

Primary database model

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

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

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.gbase.cn

github.com/spotify/heroic

sqream.com

swaydb.simer.au

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

spotify.github.io/heroic

docs.sqream.com

docs.oracle.com/database/timesten-18.1

Developer

General Data Technology Co., Ltd.

Spotify

SQream Technologies

Simer Plaha

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2004

2014

2017

2018

1998

Current release

GBase 8a, GBase 8s, GBase 8c

2022.1.6, December 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

GNU Affero GPL V3.0

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, Java, Python

Java

C++, CUDA, Haskell, Java, Scala

Scala

Server operating systems

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

Standard with numerous extensions

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

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

.Net
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

Java
Kotlin
Scala

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

user defined functions in Python

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

horizontal and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

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

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

I SQream, you SQream, we all SQream for … data analytics?
5 October 2023, Fierce Network

SQream Announces Strategic Integration for Powerful Big Data Analytics with Dataiku
9 February 2024, insideBIGDATA

SQream Joins Samsung Cloud Platform Ecosystem
26 July 2023, Datanami

SQream Technologies raises $39.4 million for GPU-accelerated databases
24 June 2020, VentureBeat

Chinese giant Alibaba leads investment round in Israel big-data startup
30 May 2018, The Times of Israel

provided by Google News

Share this page