DBMS > BigObject vs. Graphite vs. Lovefield vs. SAP SQL Anywhere

System Properties Comparison BigObject vs. Graphite vs. Lovefield vs. SAP SQL Anywhere

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Relational DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

bigobject.io

github.com/graphite-project/graphite-web

google.github.io/lovefield

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

Technical documentation

docs.bigobject.io

graphite.readthedocs.io

github.com/google/lovefield/blob/master/docs/spec_index.md

help.sap.com/docs/SAP_SQL_Anywhere

Developer

BigObject, Inc.

Chris Davis

Google

SAP

formerly Sybase

Initial release

2015

2006

2014

1992

Current release

2.1.12, February 2017

17, July 2015

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

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

Python

JavaScript

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Unix

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

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HTTP API
Sockets

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

JavaScript (Node.js)
Python

JavaScript

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

Server-side scripts

Stored procedures

Lua

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

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

locking

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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