DBMS > GigaSpaces vs. Oracle Berkeley DB vs. PostgreSQL vs. SingleStore vs. TimesTen
System Properties Comparison GigaSpaces vs. Oracle Berkeley DB vs. PostgreSQL vs. SingleStore vs. TimesTen
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Name | GigaSpaces Xexclude from comparison | Oracle Berkeley DB Xexclude from comparison | PostgreSQL Xexclude from comparison | SingleStore former name was MemSQL 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 | 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 | 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. | Relational DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Graph DBMS Search engine | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | Document store Spatial DBMS Time Series DBMS Vector DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.gigaspaces.com | www.oracle.com/database/technologies/related/berkeleydb.html | www.postgresql.org | www.singlestore.com | 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.singlestore.com | 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 | SingleStore 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 | 2013 | 1998 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 15.5, September 2020 | 18.1.40, May 2020 | 16.3, May 2024 | 8.5, January 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 | commercial free developer edition available | commercial | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Java, C++, .Net | C, Java, C++ (depending on the Berkeley DB edition) | C | C++, Go | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Linux 64 bit version required | AIX HP-UX Linux OS X Solaris SPARC/x86 Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | schema-free | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | no | yes | yes | 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 | 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 | yes but no triggers and foreign keys | 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 | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | 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 languages C C# C++ Java JavaScript (Node.js) 3rd party binding Perl Python Tcl | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | Bash C C# Java JavaScript (Node.js) Python | 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. | yes | PL/SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes, event driven architecture | yes only for the SQL API | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | none | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding hash partitioning | 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 | 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 | yes Map-Reduce pattern can be built with XAP task executors | no | no | no can define user-defined aggregate functions for map-reduce-style calculations | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency Consistency level configurable: ALL, QUORUM, ANY | Immediate Consistency | Immediate Consistency | 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 | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes, multi-version concurrency control (MVCC) | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | 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 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 | Fine grained access control via users, groups and roles | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GigaSpaces | Oracle Berkeley DB | PostgreSQL | SingleStore former name was MemSQL | TimesTen | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | SingleStore’s competitive advantages include: Easy and Simplified Architecture with... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Customers in various industries worldwide including US and International Industry... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | F ree Tier and Enterprise Edition » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GigaSpaces | Oracle Berkeley DB | PostgreSQL | SingleStore former name was MemSQL | TimesTen | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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