DBMS > CrateDB vs. Heroic vs. Realm vs. VoltDB

System Properties Comparison CrateDB vs. Heroic vs. Realm vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Time Series DBMS

Document store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	7.18
Rank	#52	Overall
	#8	Document stores

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

cratedb.com

github.com/spotify/heroic

realm.io

www.voltdb.com

Technical documentation

cratedb.com/docs

spotify.github.io/heroic

realm.io/docs

docs.voltdb.com

Developer

Crate

Spotify

Realm, acquired by MongoDB in May 2019

VoltDB Inc.

Initial release

2013

2014

2010

Current release

5.8.1, August 2024

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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.

Implementation language

Java

Java, C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Android
Backend: server-less
iOS
Windows

Linux
OS X

for development

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

.Net
Java

with Android only
Objective-C
React Native
Swift

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions (Javascript)

runs within the applications so server-side scripts are unnecessary

Java

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

yes

In-Memory realm

User concepts

Access control

rights management via user accounts

yes

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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