DBMS > BigObject vs. jBASE vs. Splice Machine vs. SWC-DB

System Properties Comparison BigObject vs. jBASE vs. Splice Machine vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

A robust multi-value DBMS comprising development tools and middleware

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

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Multivalue DBMS

Relational DBMS

Wide column store

Secondary database models

Time Series DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

bigobject.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

splicemachine.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.bigobject.io

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

splicemachine.com/how-it-works

Developer

BigObject, Inc.

Rocket Software (formerly Zumasys)

Splice Machine

Alex Kashirin

Initial release

2015

1991

2014

2020

Current release

5.7

3.1, March 2021

0.5, April 2021

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

GPL V3

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

Java

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

AIX
Linux
Windows

Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

SQL

Support of SQL

SQL-like DML and DDL statements

Embedded SQL for jBASE in BASIC

yes

SQL-like query language

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

JDBC
Native Spark Datasource
ODBC

Proprietary protocol
Thrift

Supported programming languages

.Net
Basic
Jabbascript
Java

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

C++

Server-side scripts

Stored procedures

Lua

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

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

Access rights can be defined down to the item level

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

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