DBMS > Microsoft Azure Synapse Analytics vs. Sphinx vs. WakandaDB vs. Warp 10

System Properties Comparison Microsoft Azure Synapse Analytics vs. Sphinx vs. WakandaDB vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

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

Primary database model

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

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Score	6.03
Rank	#60	Overall
	#6	Search engines

Score	0.09
Rank	#352	Overall
	#16	Object oriented DBMS

Score	0.08
Rank	#358	Overall
	#35	Time Series DBMS

Website

azure.microsoft.com/services/synapse-analytics

sphinxsearch.com

wakanda.github.io

www.warp10.io

Technical documentation

docs.microsoft.com/azure/synapse-analytics

sphinxsearch.com/docs

wakanda.github.io/doc

www.warp10.io/content/02_Getting_started

Developer

Microsoft

Sphinx Technologies Inc.

Wakanda SAS

SenX

Initial release

2016

2001

2012

2015

Current release

3.5.1, February 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

GPL version 2, commercial licence available

Open Source

AGPLv3, extended commercial license available

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

C++

C++, JavaScript

Java

Server operating systems

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

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

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
JDBC
ODBC

Proprietary protocol

RESTful HTTP API

HTTP API
Jupyter
WebSocket

Supported programming languages

C#
Java
PHP

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

JavaScript

Server-side scripts

Stored procedures

Transact SQL

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

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

yes

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

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

yes

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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