DBMS > CrateDB vs. InfinityDB vs. Redis vs. SingleStore vs. Teradata

System Properties Comparison CrateDB vs. InfinityDB vs. Redis vs. SingleStore vs. Teradata

Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

A Java embedded Key-Value Store which extends the Java Map interface

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.

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

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

Relational DBMS

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.73
Rank	#224	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	157.80
Rank	#6	Overall
	#1	Key-value stores

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

Technical documentation

cratedb.com/docs

boilerbay.com/infinitydb/manual

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

docs.singlestore.com

docs.teradata.com

Developer

Crate

Boiler Bay Inc.

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

SingleStore Inc.

Teradata

Initial release

2013

2002

2009

2013

1984

Current release

4.0

7.2.4, January 2024

8.5, January 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

commercial

Open Source

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

commercial

free developer edition available

commercial

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.

CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

Java

C++, Go

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

All OS with a Java VM

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux

64 bit version required

hosted
Linux

Data scheme

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

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

with RediSearch module

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

with RediSQL module

yes

but no triggers and foreign keys

yes

SQL 2016 + extensions

APIs and other access methods

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

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

proprietary protocol

RESP - REdis Serialization Protocol

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

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

Java

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

Bash
C
C#
Java
JavaScript (Node.js)
Python

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions (Javascript)

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

yes

UDFs, stored procedures, table functions in parallel

Triggers

publish/subscribe channels provide some trigger functionality; RedisGears

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

Sharding

hash partitioning

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

none

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Source-replica replication

stores two copies of each physical data partition on two separate nodes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

through RedisGears

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

READ-COMMITTED or SERIALIZED

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

manual creation possible, using inversions based on multi-value capability

yes

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

Optimistic locking for transactions; no isolation for bulk loads

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, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

rights management via user accounts

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 control via users, groups and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
» more

SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more

Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more

SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
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Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
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Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
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Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
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IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
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Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
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Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

See CrateDB pricing >
» more

F ree Tier and Enterprise Edition
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.