DBMS > Cassandra vs. Drizzle vs. etcd vs. Solr vs. Sqrrl

System Properties Comparison Cassandra vs. Drizzle vs. etcd vs. Solr vs. Sqrrl

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

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

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A distributed reliable key-value store

A widely used distributed, scalable search engine based on Apache Lucene

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Vector DBMS

starting with release V5

Spatial DBMS

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

Score	103.86
Rank	#12	Overall
	#1	Wide column stores

Score	7.64
Rank	#54	Overall
	#5	Key-value stores

Score	44.28
Rank	#24	Overall
	#3	Search engines

Website

cassandra.apache.org

etcd.io
github.com/etcd-io/etcd

solr.apache.org

sqrrl.com

Technical documentation

cassandra.apache.org/doc/latest

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

solr.apache.org/resources.html

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Drizzle project, originally started by Brian Aker

Apache Software Foundation

Amazon

originally Sqrrl Data, Inc.

Initial release

2008

2006

2012

Current release

4.1.3, July 2023

7.2.4, September 2012

3.4, August 2019

9.5.0, February 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GNU GPL

Open Source

Apache Version 2.0

Open Source

Apache Version 2

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C++

Java

Server operating systems

BSD
Linux
OS X
Windows

FreeBSD
Linux
OS X

FreeBSD
Linux
Windows

experimental

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux

Data scheme

schema-free

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

restricted

only equality queries, not always the best performing solution

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

yes

with proprietary extensions

Solr Parallel SQL Interface

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

JDBC

gRPC
JSON over HTTP

Java API
RESTful HTTP/JSON API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C++
Java
PHP

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Actionscript
C

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

Server-side scripts

Stored procedures

Java plugins

Triggers

yes

hooks for callbacks inside the server can be used.

yes, watching key changes

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication
Source-replica replication

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

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

Atomicity and isolation are supported for single operations

ACID

optimistic locking

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

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

Access rights for users can be defined per object

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

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

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

News

How Winweb Built its AI Assistant with DataStax Astra DB and LangChain
17 April 2024

Vercel + Astra DB: Get Data into Your GenAI Apps Fast
16 April 2024

Simplifying Agent Development with Astra DB Connector for Vertex AI Search
11 April 2024

Making Astra DB easier for MongoDB developers
10 April 2024

Empowering Enterprise GenAI: Announcing Luna for RAGStack
10 April 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.