DBMS > Brytlyt vs. GBase vs. GeoSpock vs. InfluxDB vs. Oracle

System Properties Comparison Brytlyt vs. GBase vs. GeoSpock vs. InfluxDB vs. Oracle

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

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.

Spatial and temporal data processing engine for extreme data scale

DBMS for storing time series, events and metrics

Widely used RDBMS

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Time Series DBMS

Spatial DBMS

with GEO package

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

brytlyt.io

www.gbase.cn

geospock.com

www.influxdata.com/products/influxdb-overview

www.oracle.com/database

Technical documentation

docs.brytlyt.io

docs.influxdata.com/influxdb

docs.oracle.com/en/database

Developer

Brytlyt

General Data Technology Co., Ltd.

GeoSpock

Oracle

Initial release

2016

2004

2013

1980

Current release

5.0, August 2023

GBase 8a, GBase 8s, GBase 8c

2.0, September 2019

2.7.6, April 2024

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

commercial

restricted free version is available

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, Javascript

C and C++

Server operating systems

Linux
OS X
Windows

Linux

hosted

Linux
OS X

through Homebrew

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

temporal, categorical

yes

SQL

Support of SQL

yes

Standard with numerous extensions

ANSI SQL for query only (using Presto)

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

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

ADO.NET
C API
JDBC
ODBC

JDBC

HTTP API
JSON over UDP

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

user defined functions

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Automatic sharding

Sharding

in enterprise version only

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

selectable replication factor

in enterprise version only

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

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

isolation level can be parameterized

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

Depending on used storage engine

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Access rights for users can be defined per table

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

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