DBMS > LevelDB vs. Postgres-XL vs. searchxml vs. Splice Machine

System Properties Comparison LevelDB vs. Postgres-XL vs. searchxml vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

DBMS for structured and unstructured content wrapped with an application server

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

Primary database model

Key-value store

Relational DBMS

Native XML DBMS
Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Website

github.com/google/leveldb

www.postgres-xl.org

www.searchxml.net/category/products

splicemachine.com

Technical documentation

github.com/google/leveldb/blob/main/doc/index.md

www.postgres-xl.org/documentation

www.searchxml.net/support/handouts

splicemachine.com/how-it-works

Developer

Google

informationpartners gmbh

Splice Machine

Initial release

2011

2014

since 2012, originally named StormDB

2015

2014

Current release

1.23, February 2021

10 R1, October 2018

1.0

3.1, March 2021

License

Commercial or Open Source

Open Source

BSD

Open Source

Mozilla public license

commercial

Open Source

AGPL 3.0, commercial license available

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++

Java

Server operating systems

Illumos
Linux
OS X
Windows

Linux
macOS

Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

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.

yes

XML type, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API
WebDAV
XQuery
XSLT

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++

most other programming languages supported via APIs

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

Server-side scripts

Stored procedures

user defined functions

yes

on the application server

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

sychronisation to multiple collections

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

with automatic compression on writes

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

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

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

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