DBMS > LMDB vs. Splice Machine vs. ToroDB vs. VelocityDB

System Properties Comparison LMDB vs. Splice Machine vs. ToroDB vs. VelocityDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A high performant, light-weight, embedded key-value database library

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

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

Primary database model

Key-value store

Relational DBMS

Document store

Graph DBMS
Object oriented DBMS

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

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

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

Website

www.symas.com/symas-embedded-database-lmdb

splicemachine.com

github.com/torodb/server

velocitydb.com

Technical documentation

www.lmdb.tech/doc

splicemachine.com/how-it-works

velocitydb.com/UserGuide

Developer

Symas

Splice Machine

8Kdata

VelocityDB Inc

Initial release

2011

2014

2016

2011

Current release

0.9.32, January 2024

3.1, March 2021

7.x

License

Commercial or Open Source

Open Source

AGPL 3.0, commercial license available

Open Source

AGPL-V3

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

Linux
Unix
Windows

Linux
OS X
Solaris
Windows

All OS with a Java 7 VM

Any that supports .NET

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

Supported programming languages

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

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

.Net

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

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

Eventual Consistency
Immediate Consistency

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

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 for users, groups and roles according to SQL-standard

Access rights for users and roles

Based on Windows Authentication

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