DBMS > GigaSpaces vs. Google BigQuery vs. LevelDB vs. PouchDB vs. SAP SQL Anywhere

System Properties Comparison GigaSpaces vs. Google BigQuery vs. LevelDB vs. PouchDB vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Large scale data warehouse service with append-only tables

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

JavaScript DBMS with an API inspired by CouchDB

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

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Secondary database models

Graph DBMS
Search engine

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

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

www.gigaspaces.com

cloud.google.com/bigquery

github.com/google/leveldb

pouchdb.com

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

Technical documentation

docs.gigaspaces.com/latest/landing.html

cloud.google.com/bigquery/docs

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

pouchdb.com/guides

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Gigaspaces Technologies

Google

Apache Software Foundation

SAP

formerly Sybase

Initial release

2000

2010

2011

2012

1992

Current release

15.5, September 2020

1.23, February 2021

7.1.1, June 2019

17, July 2015

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

BSD

Open Source

commercial

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

Java, C++, .Net

C++

JavaScript

Server operating systems

Linux
macOS
Solaris
Windows

hosted

Illumos
Linux
OS X
Windows

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

AIX
HP-UX
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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

JavaScript

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

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

View functions in JavaScript

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

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

Role-based access control

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

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