DBMS > Apache Drill vs. Cassandra vs. EJDB vs. Google Cloud Spanner vs. KairosDB

System Properties Comparison Apache Drill vs. Cassandra vs. EJDB vs. Google Cloud Spanner vs. KairosDB

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Distributed Time Series DBMS based on Cassandra or H2

Primary database model

Document store
Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Website

drill.apache.org

cassandra.apache.org

github.com/Softmotions/ejdb

cloud.google.com/spanner

github.com/kairosdb/kairosdb

Technical documentation

drill.apache.org/docs

cassandra.apache.org/doc/latest

github.com/Softmotions/ejdb/blob/master/README.md

cloud.google.com/spanner/docs

kairosdb.github.io

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Softmotions

Google

Initial release

2012

2008

2012

2017

2013

Current release

1.20.3, January 2023

4.1.3, July 2023

1.2.2, November 2018

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache version 2

Open Source

GPLv2

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Windows

server-less

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

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

yes

Query statements complying to ANSI 2011

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Proprietary protocol

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

in-process shared library

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

C++

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

none

Multi-source replication with 3 replicas for regional instances.

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Strict serializable isolation

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

User concepts

Access control

Depending on the underlying data source

Access rights for users can be defined per object

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

simple password-based access control

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

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