DBMS > Galaxybase vs. Interbase vs. RocksDB vs. Splice Machine

System Properties Comparison Galaxybase vs. Interbase vs. RocksDB vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

Scalable, ACID-compliant native distributed parallel graph platform

Light-weight proven RDBMS

originally from Borland

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

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

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

galaxybase.com

www.embarcadero.com/products/interbase

rocksdb.org

splicemachine.com

Technical documentation

docs.embarcadero.com/products/interbase

github.com/facebook/rocksdb/wiki

splicemachine.com/how-it-works

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Embarcadero

Facebook, Inc.

Splice Machine

Initial release

2017

1984

2013

2014

Current release

Nov 20, November 2021

InterBase 2020, December 2019

8.11.4, April 2024

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

AGPL 3.0, commercial license available

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 and Java

C++

Java

Server operating systems

Linux

Android
iOS
Linux
OS X
Windows

Linux

Linux
OS X
Solaris
Windows

Data scheme

Strong typed schema

yes

schema-free

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.

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

ADO.NET
JDBC
ODBC

C++ API
Java API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Go
Java
Python

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

C
C++
Go
Java
Perl
Python
Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

user defined procedures and functions

yes

Interbase procedure and trigger language

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Interbase Change Views

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

yes, multi-version concurrency control (MVCC)

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

Role-based access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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