DBMS > Realm vs. Splice Machine vs. VelocityDB vs. Yaacomo

System Properties Comparison Realm vs. Splice Machine vs. VelocityDB vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store

Relational DBMS

Graph DBMS
Object oriented DBMS

Relational DBMS

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

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

realm.io

splicemachine.com

velocitydb.com

yaacomo.com

Technical documentation

realm.io/docs

splicemachine.com/how-it-works

velocitydb.com/UserGuide

Developer

Realm, acquired by MongoDB in May 2019

Splice Machine

VelocityDB Inc

Q2WEB GmbH

Initial release

2014

2011

2009

Current release

3.1, March 2021

7.x

License

Commercial or Open Source

Open Source

AGPL 3.0, commercial license available

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

Java

Server operating systems

Android
Backend: server-less
iOS
Windows

Linux
OS X
Solaris
Windows

Any that supports .NET

Android
Linux
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
Native Spark Datasource
ODBC

.Net

JDBC
ODBC

Supported programming languages

.Net
Java

with Android only
Objective-C
React Native
Swift

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

.Net

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

yes

Java

Triggers

yes

Change Listeners

yes

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica 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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

In-Memory realm

yes

User concepts

Access control

yes

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

Based on Windows Authentication

fine grained access rights according to SQL-standard

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More resources

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