DBMS > Apache Druid vs. Realm vs. Redis vs. SAP SQL Anywhere vs. Splice Machine

System Properties Comparison Apache Druid vs. Realm vs. Redis vs. SAP SQL Anywhere vs. Splice Machine

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

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

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Relational DBMS
Time Series DBMS

Document store

Key-value store

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Relational DBMS

Secondary database models

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	7.18
Rank	#52	Overall
	#8	Document stores

Score	149.43
Rank	#6	Overall
	#1	Key-value stores

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Website

druid.apache.org

realm.io

redis.com
redis.io

www.sap.com/products/technology-platform/sql-anywhere.html

splicemachine.com

Technical documentation

druid.apache.org/docs/latest/design

realm.io/docs

docs.redis.com/latest/index.html
redis.io/docs

help.sap.com/docs/SAP_SQL_Anywhere

splicemachine.com/how-it-works

Developer

Apache Software Foundation and contributors

Realm, acquired by MongoDB in May 2019

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

SAP

formerly Sybase

Splice Machine

Initial release

2012

2014

2009

1992

2014

Current release

30.0.0, June 2024

7.2.5, May 2024

17, July 2015

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

commercial

Open Source

AGPL 3.0, commercial license available

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

Server operating systems

Linux
OS X
Unix

Android
Backend: server-less
iOS
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-less columns are supported

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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.

yes

Secondary indexes

yes

with RediSearch module

yes

SQL

Support of SQL

SQL for querying

with RediSQL module

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
HTTP API
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
Java

with Android only
Objective-C
React Native
Swift

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

Lua; Redis Functions coming in Redis 7 (slides and Github)

yes, in C/C++, Java, .Net or Perl

yes

Java

Triggers

yes

Change Listeners

publish/subscribe channels provide some trigger functionality; RedisGears

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Source-replica replication

Database mirroring

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

through RedisGears

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts and optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

In-memory capabilities

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

yes

In-Memory realm

yes

User concepts

Access control

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

yes

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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