DBMS > Apache Druid vs. Google Cloud Spanner vs. HEAVY.AI vs. JSqlDb vs. RocksDB

System Properties Comparison Apache Druid vs. Google Cloud Spanner vs. HEAVY.AI vs. JSqlDb vs. RocksDB

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

JavaScript Query Language Database, stores JavaScript objects and primitives

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

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Document store
Object oriented DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

druid.apache.org

cloud.google.com/spanner

github.com/heavyai/heavydb
www.heavy.ai

jsqldb.org (offline)

rocksdb.org

Technical documentation

druid.apache.org/docs/latest/design

cloud.google.com/spanner/docs

docs.heavy.ai

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

Google

HEAVY.AI, Inc.

Konrad von Backstrom

Facebook, Inc.

Initial release

2012

2017

2016

2018

2013

Current release

29.0.1, April 2024

5.10, January 2022

0.8, December 2018

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

BSD

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

C++ and CUDA

C++

Server operating systems

Linux
OS X
Unix

hosted

Linux

Linux
macOS
Windows

Linux

Data scheme

yes

schema-less columns are supported

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

gRPC (using protocol buffers) API
JDBC

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

JDBC
ODBC
Thrift
Vega

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

functions in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

Round robin

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication with 3 replicas for regional instances.

Multi-source replication

none

yes

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

Immediate Consistency

Foreign keys

Referential integrity

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

ACID

Strict serializable isolation

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

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

fine grained access rights according to SQL-standard

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