DBMS > DolphinDB vs. Google BigQuery vs. SAP Advantage Database Server vs. Sphinx vs. Warp 10

System Properties Comparison DolphinDB vs. Google BigQuery vs. SAP Advantage Database Server vs. Sphinx vs. Warp 10

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Large scale data warehouse service with append-only tables

Low-cost RDBMS with access to ISAM and FoxPro data structures

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

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

Primary database model

Secondary database models

Relational DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

www.dolphindb.com

cloud.google.com/bigquery

www.sap.com/products/advantage-database-server.html

sphinxsearch.com

www.warp10.io

Technical documentation

docs.dolphindb.cn/en/help200/index.html

cloud.google.com/bigquery/docs

sphinxsearch.com/docs

www.warp10.io/content/02_Getting_started

Developer

DolphinDB, Inc

Google

Sybase, SAP

Sphinx Technologies Inc.

SenX

Initial release

2018

2010

1993

2001

2015

Current release

v2.00.4, January 2022

3.5.1, February 2023

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

GPL version 2, commercial licence 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++

Java

Server operating systems

Linux
Windows

hosted

Linux
Windows

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

SQL-like query language

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

RESTful HTTP/JSON API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Proprietary protocol

HTTP API
Jupyter
WebSocket

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Delphi
Perl
PHP

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

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

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Since BigQuery is designed for querying 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

caching of (temporary) tables can be configured

yes

User concepts

Access control

Administrators, Users, Groups

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.