DBMS > AlaSQL vs. GeoSpock vs. Sphinx vs. SQLite vs. Warp 10

System Properties Comparison AlaSQL vs. GeoSpock vs. Sphinx vs. SQLite vs. Warp 10

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

JavaScript DBMS library

Spatial and temporal data processing engine for extreme data scale

Open source search engine for searching in data from different sources, e.g. relational databases

Widely used embeddable, in-process RDBMS

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Document store
Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

geospock.com

Technical documentation

github.com/AlaSQL/alasql

sphinxsearch.com/docs

www.sqlite.org/docs.html

www.warp10.io/content/02_Getting_started

Developer

Andrey Gershun & Mathias R. Wulff

GeoSpock

Sphinx Technologies Inc.

Dwayne Richard Hipp

SenX

Initial release

2014

2001

2000

2015

Current release

2.0, September 2019

3.5.1, February 2023

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

GPL version 2, commercial licence available

Open Source

Public Domain

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Java, Javascript

C++

Java

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

server-less

Linux
OS X
Windows

Data scheme

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

temporal, categorical

yes

full-text index on all search fields

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

ANSI SQL for query only (using Presto)

SQL-like query language (SphinxQL)

yes

SQL-92 is not fully supported

APIs and other access methods

JavaScript API

JDBC

Proprietary protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

HTTP API
Jupyter
WebSocket

Supported programming languages

JavaScript

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

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

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

The original contents of fields are not stored in the Sphinx index.

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 can be defined per table

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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