DBMS > Apache Druid vs. Dragonfly vs. LeanXcale vs. SAP SQL Anywhere vs. SQLite

System Properties Comparison Apache Druid vs. Dragonfly vs. LeanXcale vs. SAP SQL Anywhere vs. SQLite

Editorial information provided by DB-Engines

Name

Description

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

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

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

Key-value store
Relational DBMS

Relational DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

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

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

druid.apache.org

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.leanxcale.com

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

www.sqlite.org

Technical documentation

druid.apache.org/docs/latest/design

www.dragonflydb.io/docs

help.sap.com/docs/SAP_SQL_Anywhere

www.sqlite.org/docs.html

Developer

Apache Software Foundation and contributors

DragonflyDB team and community contributors

LeanXcale

SAP

formerly Sybase

Dwayne Richard Hipp

Initial release

2012

2023

2015

1992

2000

Current release

29.0.1, April 2024

1.0, March 2023

17, July 2015

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

BSL 1.1

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

server-less

Data scheme

yes

schema-less columns are supported

scheme-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

yes

not rigid because of 'dynamic typing' concept.

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 for querying

yes

through Apache Derby

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
HTTP API
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

C
Java
Scala

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

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

Server-side scripts

Stored procedures

Lua

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

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

Database mirroring

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

via file-system locks

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

Password-based authentication

fine grained access rights according to SQL-standard

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