DBMS > Apache Druid vs. Datastax Enterprise vs. GigaSpaces vs. RocksDB

System Properties Comparison Apache Druid vs. Datastax Enterprise vs. GigaSpaces vs. RocksDB

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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

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS
Time Series DBMS

Wide column store

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Graph DBMS
Search engine

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

Score	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	6.31
Rank	#57	Overall
	#4	Wide column stores

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

druid.apache.org

www.datastax.com/products/datastax-enterprise

www.gigaspaces.com

rocksdb.org

Technical documentation

druid.apache.org/docs/latest/design

docs.datastax.com

docs.gigaspaces.com/latest/landing.html

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

DataStax

Gigaspaces Technologies

Facebook, Inc.

Initial release

2012

2011

2000

2013

Current release

29.0.1, April 2024

6.8, April 2020

15.5, September 2020

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

BSD

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.

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Implementation language

Java

Java, C++, .Net

C++

Server operating systems

Linux
OS X
Unix

Linux
OS X

Linux
macOS
Solaris
Windows

Linux

Data scheme

yes

schema-less columns are supported

schema-free

Typing

predefined data types such as float or date

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

SQL-like DML and DDL statements (CQL); Spark SQL

SQL-99 for query and DML statements

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

.Net
C++
Java
Python
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

no "single point of failure"

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

configurable replication factor, datacenter aware, advanced replication for edge computing

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Foreign keys

Referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

yes

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

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

Access rights for users can be defined per object

Role-based access control

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

Annual subscription
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