DBMS > Apache Druid vs. GeoMesa vs. IBM Db2 Event Store vs. RocksDB vs. Rockset

System Properties Comparison Apache Druid vs. GeoMesa vs. IBM Db2 Event Store vs. RocksDB vs. Rockset

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Distributed Event Store optimized for Internet of Things use cases

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

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS
Time Series DBMS

Spatial DBMS

Event Store
Time Series DBMS

Key-value store

Document store

Secondary database models

Relational DBMS
Search engine

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	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

druid.apache.org

www.geomesa.org

www.ibm.com/products/db2-event-store

rocksdb.org

rockset.com

Technical documentation

druid.apache.org/docs/latest/design

www.geomesa.org/documentation/stable/user/index.html

www.ibm.com/docs/en/db2-event-store

github.com/facebook/rocksdb/wiki

docs.rockset.com

Developer

Apache Software Foundation and contributors

CCRi and others

IBM

Facebook, Inc.

Rockset

Initial release

2012

2014

2017

2013

2019

Current release

29.0.1, April 2024

4.0.5, February 2024

2.0

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache License 2.0

commercial

free developer edition available

Open Source

BSD

commercial

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.

Implementation language

Java

Scala

C and C++

C++

Server operating systems

Linux
OS X
Unix

Linux

Linux, macOS, Windows for the developer addition

Linux

hosted

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

SQL for querying

yes

through the embedded Spark runtime

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

C++ API
Java API

HTTP REST

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C
C++
Go
Java
Perl
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

depending on storage layer

Sharding

horizontal partitioning

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

depending on storage layer

Active-active shard replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

In-memory capabilities

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

depending on storage layer

yes

User concepts

Access control

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

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

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