DBMS > LMDB vs. RocksDB vs. Spark SQL vs. TerminusDB

System Properties Comparison LMDB vs. RocksDB vs. Spark SQL vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

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

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Key-value store

Relational DBMS

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

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

rocksdb.org

spark.apache.org/sql

terminusdb.com

Technical documentation

www.lmdb.tech/doc

github.com/facebook/rocksdb/wiki

spark.apache.org/docs/latest/sql-programming-guide.html

terminusdb.github.io/terminusdb/#

Developer

Symas

Facebook, Inc.

Apache Software Foundation

DataChemist Ltd.

Initial release

2011

2013

2014

2018

Current release

0.9.32, January 2024

9.2.1, May 2024

3.5.0 ( 2.13), September 2023

11.0.0, January 2023

License

Commercial or Open Source

Open Source

BSD

Open Source

Apache 2.0

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

C++

Scala

Prolog, Rust

Server operating systems

Linux
Unix
Windows

Linux

Linux
OS X
Windows

Linux

Data scheme

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.

Secondary indexes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (WOQL)

APIs and other access methods

C++ API
Java API

JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

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++
Go
Java
Perl
Python
Ruby

Java
Python
R
Scala

JavaScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

yes, utilizing Spark Core

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

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