DBMS > GigaSpaces vs. Oracle Berkeley DB vs. PostgreSQL vs. Redis vs. TimesTen
System Properties Comparison GigaSpaces vs. Oracle Berkeley DB vs. PostgreSQL vs. Redis vs. TimesTen
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| Name | GigaSpaces Xexclude from comparison | Oracle Berkeley DB Xexclude from comparison | PostgreSQL Xexclude from comparison | Redis Xexclude from comparison | TimesTen Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions | Widely used in-process key-value store | Widely used open source RDBMS  Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | 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. | In-Memory RDBMS compatible to Oracle | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Document store Object oriented DBMS Values are user defined objects | Key-value store supports sorted and unsorted key sets Native XML DBMS in the Oracle Berkeley DB XML version | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | 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 | Graph DBMS Search engine | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | Document store with RedisJSON Graph DBMS with RedisGraphSpatial DBMS Search engine with RediSearchTime Series DBMS with RedisTimeSeriesVector DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.gigaspaces.com | www.oracle.com/database/technologies/related/berkeleydb.html | www.postgresql.org | redis.com redis.io | www.oracle.com/database/technologies/related/timesten.html | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.gigaspaces.com/latest/landing.html | docs.oracle.com/cd/E17076_05/html/index.html | www.postgresql.org/docs | docs.redis.com/latest/index.html redis.io/docs | docs.oracle.com/database/timesten-18.1 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Gigaspaces Technologies | Oracle originally developed by Sleepycat, which was acquired by Oracle | PostgreSQL Global Development Group www.postgresql.org/developer | Redis project core team, inspired by Salvatore Sanfilippo Development sponsored by Redis Inc. | Oracle, TimesTen Performance Software, HP originally founded in HP Labs it was acquired by Oracle in 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2000 | 1994 | 1989 1989: Postgres, 1996: PostgreSQL | 2009 | 1998 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 15.5, September 2020 | 18.1.40, May 2020 | 16.3, May 2024 | 7.2.5, May 2024 | 11 Release 2 (11.2.2.8.0) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source Apache Version 2; Commercial licenses available | Open Source commercial license available | Open Source BSD | Open Source source-available extensions (modules), commercial licenses for Redis Enterprise | commercial | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | Java, C++, .Net | C, Java, C++ (depending on the Berkeley DB edition) | C | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux macOS Solaris Windows | AIX Android FreeBSD iOS Linux OS X Solaris VxWorks Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | BSD Linux OS X Windows ported and maintained by Microsoft Open Technologies, Inc. | AIX HP-UX Linux OS X Solaris SPARC/x86 Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | schema-free | yes | schema-free | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | no | 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. | no XML can be used for describing objects metadata | yes only with the Berkeley DB XML edition | yes specific XML-type available, but no XML query functionality. | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | yes | yes with RediSearch module | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL-99 for query and DML statements | yes SQL interfaced based on SQLite is available | yes standard with numerous extensions | with RediSQL module | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | GigaSpaces LRMI Hibernate JCache JDBC JPA ODBC RESTful HTTP API Spring Data | ADO.NET JDBC native C library ODBC streaming API for large objects | proprietary protocol RESP - REdis Serialization Protocol | JDBC ODBC ODP.NET Oracle Call Interface (OCI) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net C++ Java Python Scala | .Net Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET others Third-party libraries to manipulate Berkeley DB files are available for many languagesC C# C++ Java JavaScript (Node.js) 3rd party bindingPerl Python Tcl | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | 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++ Java PL/SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | Lua; Redis Functions coming in Redis 7 (slides and Github) | PL/SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes, event driven architecture | yes only for the SQL API | yes | publish/subscribe channels provide some trigger functionality; RedisGears | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding | none | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding Automatic hash-based sharding with support for hash-tags for manual sharding | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication synchronous or asynchronous Source-replica replication synchronous or asynchronous | Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | Multi-source replication with Redis Enterprise Pack Source-replica replication Chained replication is supported | Multi-source replication Source-replica replication | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | yes Map-Reduce pattern can be built with XAP task executors | no | no | through RedisGears | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency Consistency level configurable: ALL, QUORUM, ANY | 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 or Eventual Consistency depending on configuration | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID | ACID | Atomic execution of command blocks and scripts and optimistic locking | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes Data access is serialized by the server | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes Configurable mechanisms for persistency via snapshots and/or operations logs | yes by means of logfiles and checkpoints | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Role-based access control | no | fine grained access rights according to SQL-standard | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 3rd parties | Fujitsu Enterprise Postgres: An Enterprise Grade PostgreSQL with the flexibility of a hybrid cloud solution combined with industry leading security, availability and performance.
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| GigaSpaces | Oracle Berkeley DB | PostgreSQL | Redis | TimesTen | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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