DBMS > Apache Druid vs. Geode vs. SQLite vs. Sqrrl

System Properties Comparison Apache Druid vs. Geode vs. SQLite vs. Sqrrl

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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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Widely used embeddable, in-process RDBMS

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

druid.apache.org

geode.apache.org

www.sqlite.org

sqrrl.com

Technical documentation

druid.apache.org/docs/latest/design

geode.apache.org/docs

www.sqlite.org/docs.html

Developer

Apache Software Foundation and contributors

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Dwayne Richard Hipp

Amazon

originally Sqrrl Data, Inc.

Initial release

2012

2002

2000

2012

Current release

29.0.1, April 2024

1.1, February 2017

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Public Domain

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

Java

Server operating systems

Linux
OS X
Unix

All OS with a Java VM

the JDK (8 or later) is also required

server-less

Linux

Data scheme

yes

schema-less columns are supported

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL for querying

SQL-like query language (OQL)

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Java Client API
Memcached protocol
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
All JVM based languages
C++
Groovy
Java
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Actionscript
C

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

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication

none

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

Immediate Consistency

Eventual Consistency

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

yes, on a single node

ACID

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights per client and object definable

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

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