DBMS > LeanXcale vs. SAP SQL Anywhere vs. searchxml vs. Splice Machine vs. SQLite

System Properties Comparison LeanXcale vs. SAP SQL Anywhere vs. searchxml vs. Splice Machine vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Native XML DBMS
Search engine

Relational DBMS

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

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.leanxcale.com

www.sap.com/products/technology-platform/sql-anywhere.html

www.searchxml.net/category/products

splicemachine.com

www.sqlite.org

Technical documentation

help.sap.com/docs/SAP_SQL_Anywhere

www.searchxml.net/support/handouts

splicemachine.com/how-it-works

www.sqlite.org/docs.html

Developer

LeanXcale

SAP

formerly Sybase

informationpartners gmbh

Splice Machine

Dwayne Richard Hipp

Initial release

2015

1992

2015

2014

2000

Current release

17, July 2015

1.0

3.1, March 2021

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

Public Domain

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

AIX
HP-UX
Linux
OS X
Solaris
Windows

Windows

Linux
OS X
Solaris
Windows

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
HTTP API
JDBC
ODBC

RESTful HTTP API
WebDAV
XQuery
XSLT

JDBC
Native Spark Datasource
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
Java
Scala

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C++

most other programming languages supported via APIs

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes, in C/C++, Java, .Net or Perl

yes

on the application server

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Database mirroring

yes

sychronisation to multiple collections

Multi-source replication
Source-replica replication

none

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

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

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

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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