DBMS > BigObject vs. Dolt vs. Hyprcubd vs. Splice Machine

System Properties Comparison BigObject vs. Dolt vs. Hyprcubd vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Analytic DBMS for real-time computations and queries

A MySQL compatible DBMS with Git-like versioning of data and schema

Serverless Time Series DBMS

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

bigobject.io

github.com/dolthub/dolt
www.dolthub.com

hyprcubd.com (offline)

splicemachine.com

Technical documentation

docs.bigobject.io

docs.dolthub.com

splicemachine.com/how-it-works

Developer

BigObject, Inc.

DoltHub Inc

Hyprcubd, Inc.

Splice Machine

Initial release

2015

2018

2014

Current release

3.1, March 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2.0

commercial

Open Source

AGPL 3.0, commercial license 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

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
macOS
Windows

hosted

Linux
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

CLI Client
HTTP REST

gRPC (https)

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

Lua

yes

currently in alpha release

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

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

Eventual Consistency

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)

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

Only one user is configurable, and must be specified in the config file at startup

token access

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

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More resources

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