DBMS > Graphite vs. H2GIS vs. LeanXcale vs. Sqrrl vs. Valentina Server

System Properties Comparison Graphite vs. H2GIS vs. LeanXcale vs. Sqrrl vs. Valentina Server

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Spatial extension of H2

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Adaptable, secure NoSQL built on Apache Accumulo

Object-relational database and reports server

Primary database model

Time Series DBMS

Spatial DBMS

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

github.com/graphite-project/graphite-web

www.h2gis.org

www.leanxcale.com

sqrrl.com

www.valentina-db.net

Technical documentation

graphite.readthedocs.io

www.h2gis.org/docs/home

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Chris Davis

CNRS

LeanXcale

Amazon

originally Sqrrl Data, Inc.

Paradigma Software

Initial release

2006

2013

2015

2012

1999

Current release

5.7.5

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

LGPL 3.0

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

Java

Server operating systems

Linux
Unix

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

yes

APIs and other access methods

HTTP API
Sockets

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

ODBC

Supported programming languages

JavaScript (Node.js)
Python

Java

C
Java
Scala

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

based on H2

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

based on H2

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

locking

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

based on H2

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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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Recent citations in the news

Try out the Graphite monitoring tool for time-series data
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23 January 2018, CNBC

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18 September 2023, Mint

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